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2686b0d4a10f365b8e51c3dc4941937c95b07ca7 |
# Dataset Card for `codesearchnet/challenge`
The `codesearchnet/challenge` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/codesearchnet#codesearchnet/challenge).
# Data
This dataset provides:
- `queries` (i.e., topics); count=99
- `qrels`: (relevance assessments); count=4,006
- For `docs`, use [`irds/codesearchnet`](https://huggingface.co/datasets/irds/codesearchnet)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/codesearchnet_challenge', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/codesearchnet_challenge', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'note': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Husain2019CodeSearchNet,
title={CodeSearchNet Challenge: Evaluating the State of Semantic Code Search},
author={Hamel Husain and Ho-Hsiang Wu and Tiferet Gazit and Miltiadis Allamanis and Marc Brockschmidt},
journal={ArXiv},
year={2019}
}
```
| irds/codesearchnet_challenge | [
"task_categories:text-retrieval",
"source_datasets:irds/codesearchnet",
"region:us"
] | 2023-01-05T03:03:31+00:00 | {"source_datasets": ["irds/codesearchnet"], "task_categories": ["text-retrieval"], "pretty_name": "`codesearchnet/challenge`", "viewer": false} | 2023-01-05T03:03:37+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/codesearchnet #region-us
|
# Dataset Card for 'codesearchnet/challenge'
The 'codesearchnet/challenge' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=99
- 'qrels': (relevance assessments); count=4,006
- For 'docs', use 'irds/codesearchnet'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'codesearchnet/challenge'\n\nThe 'codesearchnet/challenge' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=99\n - 'qrels': (relevance assessments); count=4,006\n\n - For 'docs', use 'irds/codesearchnet'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/codesearchnet #region-us \n",
"# Dataset Card for 'codesearchnet/challenge'\n\nThe 'codesearchnet/challenge' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=99\n - 'qrels': (relevance assessments); count=4,006\n\n - For 'docs', use 'irds/codesearchnet'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
853bf8f7923e1d3f916fecf38d4a437bb64ec18c |
# Dataset Card for `codesearchnet/test`
The `codesearchnet/test` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/codesearchnet#codesearchnet/test).
# Data
This dataset provides:
- `queries` (i.e., topics); count=100,529
- `qrels`: (relevance assessments); count=100,529
- For `docs`, use [`irds/codesearchnet`](https://huggingface.co/datasets/irds/codesearchnet)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/codesearchnet_test', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/codesearchnet_test', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Husain2019CodeSearchNet,
title={CodeSearchNet Challenge: Evaluating the State of Semantic Code Search},
author={Hamel Husain and Ho-Hsiang Wu and Tiferet Gazit and Miltiadis Allamanis and Marc Brockschmidt},
journal={ArXiv},
year={2019}
}
```
| irds/codesearchnet_test | [
"task_categories:text-retrieval",
"source_datasets:irds/codesearchnet",
"region:us"
] | 2023-01-05T03:03:42+00:00 | {"source_datasets": ["irds/codesearchnet"], "task_categories": ["text-retrieval"], "pretty_name": "`codesearchnet/test`", "viewer": false} | 2023-01-05T03:03:48+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/codesearchnet #region-us
|
# Dataset Card for 'codesearchnet/test'
The 'codesearchnet/test' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=100,529
- 'qrels': (relevance assessments); count=100,529
- For 'docs', use 'irds/codesearchnet'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'codesearchnet/test'\n\nThe 'codesearchnet/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=100,529\n - 'qrels': (relevance assessments); count=100,529\n\n - For 'docs', use 'irds/codesearchnet'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/codesearchnet #region-us \n",
"# Dataset Card for 'codesearchnet/test'\n\nThe 'codesearchnet/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=100,529\n - 'qrels': (relevance assessments); count=100,529\n\n - For 'docs', use 'irds/codesearchnet'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
2387d7238e065304190aa0b769c9e7256e29e6d9 |
# Dataset Card for `codesearchnet/train`
The `codesearchnet/train` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/codesearchnet#codesearchnet/train).
# Data
This dataset provides:
- `queries` (i.e., topics); count=1,880,853
- `qrels`: (relevance assessments); count=1,880,853
- For `docs`, use [`irds/codesearchnet`](https://huggingface.co/datasets/irds/codesearchnet)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/codesearchnet_train', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/codesearchnet_train', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Husain2019CodeSearchNet,
title={CodeSearchNet Challenge: Evaluating the State of Semantic Code Search},
author={Hamel Husain and Ho-Hsiang Wu and Tiferet Gazit and Miltiadis Allamanis and Marc Brockschmidt},
journal={ArXiv},
year={2019}
}
```
| irds/codesearchnet_train | [
"task_categories:text-retrieval",
"source_datasets:irds/codesearchnet",
"region:us"
] | 2023-01-05T03:03:53+00:00 | {"source_datasets": ["irds/codesearchnet"], "task_categories": ["text-retrieval"], "pretty_name": "`codesearchnet/train`", "viewer": false} | 2023-01-05T03:03:59+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/codesearchnet #region-us
|
# Dataset Card for 'codesearchnet/train'
The 'codesearchnet/train' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=1,880,853
- 'qrels': (relevance assessments); count=1,880,853
- For 'docs', use 'irds/codesearchnet'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'codesearchnet/train'\n\nThe 'codesearchnet/train' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=1,880,853\n - 'qrels': (relevance assessments); count=1,880,853\n\n - For 'docs', use 'irds/codesearchnet'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/codesearchnet #region-us \n",
"# Dataset Card for 'codesearchnet/train'\n\nThe 'codesearchnet/train' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=1,880,853\n - 'qrels': (relevance assessments); count=1,880,853\n\n - For 'docs', use 'irds/codesearchnet'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
20e11b36196452db968cf0e9aa62203728c7c9b1 |
# Dataset Card for `codesearchnet/valid`
The `codesearchnet/valid` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/codesearchnet#codesearchnet/valid).
# Data
This dataset provides:
- `queries` (i.e., topics); count=89,154
- `qrels`: (relevance assessments); count=89,154
- For `docs`, use [`irds/codesearchnet`](https://huggingface.co/datasets/irds/codesearchnet)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/codesearchnet_valid', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/codesearchnet_valid', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Husain2019CodeSearchNet,
title={CodeSearchNet Challenge: Evaluating the State of Semantic Code Search},
author={Hamel Husain and Ho-Hsiang Wu and Tiferet Gazit and Miltiadis Allamanis and Marc Brockschmidt},
journal={ArXiv},
year={2019}
}
```
| irds/codesearchnet_valid | [
"task_categories:text-retrieval",
"source_datasets:irds/codesearchnet",
"region:us"
] | 2023-01-05T03:04:05+00:00 | {"source_datasets": ["irds/codesearchnet"], "task_categories": ["text-retrieval"], "pretty_name": "`codesearchnet/valid`", "viewer": false} | 2023-01-05T03:04:10+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/codesearchnet #region-us
|
# Dataset Card for 'codesearchnet/valid'
The 'codesearchnet/valid' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=89,154
- 'qrels': (relevance assessments); count=89,154
- For 'docs', use 'irds/codesearchnet'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'codesearchnet/valid'\n\nThe 'codesearchnet/valid' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=89,154\n - 'qrels': (relevance assessments); count=89,154\n\n - For 'docs', use 'irds/codesearchnet'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/codesearchnet #region-us \n",
"# Dataset Card for 'codesearchnet/valid'\n\nThe 'codesearchnet/valid' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=89,154\n - 'qrels': (relevance assessments); count=89,154\n\n - For 'docs', use 'irds/codesearchnet'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
f6b24444633ecf2c5790e7bef324c304ea186e6d |
# Dataset Card for `gov`
The `gov` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov#gov).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=1,247,753
This dataset is used by: [`gov_trec-web-2002`](https://huggingface.co/datasets/irds/gov_trec-web-2002), [`gov_trec-web-2002_named-page`](https://huggingface.co/datasets/irds/gov_trec-web-2002_named-page), [`gov_trec-web-2003`](https://huggingface.co/datasets/irds/gov_trec-web-2003), [`gov_trec-web-2003_named-page`](https://huggingface.co/datasets/irds/gov_trec-web-2003_named-page), [`gov_trec-web-2004`](https://huggingface.co/datasets/irds/gov_trec-web-2004)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/gov', 'docs')
for record in docs:
record # {'doc_id': ..., 'url': ..., 'http_headers': ..., 'body': ..., 'body_content_type': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
| irds/gov | [
"task_categories:text-retrieval",
"region:us"
] | 2023-01-05T03:04:16+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`gov`", "viewer": false} | 2023-01-05T03:04:22+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #region-us
|
# Dataset Card for 'gov'
The 'gov' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=1,247,753
This dataset is used by: 'gov_trec-web-2002', 'gov_trec-web-2002_named-page', 'gov_trec-web-2003', 'gov_trec-web-2003_named-page', 'gov_trec-web-2004'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov'\n\nThe 'gov' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=1,247,753\n\n\nThis dataset is used by: 'gov_trec-web-2002', 'gov_trec-web-2002_named-page', 'gov_trec-web-2003', 'gov_trec-web-2003_named-page', 'gov_trec-web-2004'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #region-us \n",
"# Dataset Card for 'gov'\n\nThe 'gov' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=1,247,753\n\n\nThis dataset is used by: 'gov_trec-web-2002', 'gov_trec-web-2002_named-page', 'gov_trec-web-2003', 'gov_trec-web-2003_named-page', 'gov_trec-web-2004'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
503f29b4667d239494c65d0f5cd938780c471914 |
# Dataset Card for `gov/trec-web-2002`
The `gov/trec-web-2002` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov#gov/trec-web-2002).
# Data
This dataset provides:
- `queries` (i.e., topics); count=50
- `qrels`: (relevance assessments); count=56,650
- For `docs`, use [`irds/gov`](https://huggingface.co/datasets/irds/gov)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov_trec-web-2002', 'queries')
for record in queries:
record # {'query_id': ..., 'title': ..., 'description': ..., 'narrative': ...}
qrels = load_dataset('irds/gov_trec-web-2002', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Craswell2002TrecWeb,
title={Overview of the TREC-2002 Web Track},
author={Nick Craswell and David Hawking},
booktitle={TREC},
year={2002}
}
```
| irds/gov_trec-web-2002 | [
"task_categories:text-retrieval",
"source_datasets:irds/gov",
"region:us"
] | 2023-01-05T03:04:27+00:00 | {"source_datasets": ["irds/gov"], "task_categories": ["text-retrieval"], "pretty_name": "`gov/trec-web-2002`", "viewer": false} | 2023-01-05T03:04:33+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov #region-us
|
# Dataset Card for 'gov/trec-web-2002'
The 'gov/trec-web-2002' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=50
- 'qrels': (relevance assessments); count=56,650
- For 'docs', use 'irds/gov'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov/trec-web-2002'\n\nThe 'gov/trec-web-2002' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=50\n - 'qrels': (relevance assessments); count=56,650\n\n - For 'docs', use 'irds/gov'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov #region-us \n",
"# Dataset Card for 'gov/trec-web-2002'\n\nThe 'gov/trec-web-2002' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=50\n - 'qrels': (relevance assessments); count=56,650\n\n - For 'docs', use 'irds/gov'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
e78f05cb38dbfac1c3b0c50546cb475b49a229e6 |
# Dataset Card for `gov/trec-web-2002/named-page`
The `gov/trec-web-2002/named-page` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov#gov/trec-web-2002/named-page).
# Data
This dataset provides:
- `queries` (i.e., topics); count=150
- `qrels`: (relevance assessments); count=170
- For `docs`, use [`irds/gov`](https://huggingface.co/datasets/irds/gov)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov_trec-web-2002_named-page', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/gov_trec-web-2002_named-page', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Craswell2002TrecWeb,
title={Overview of the TREC-2002 Web Track},
author={Nick Craswell and David Hawking},
booktitle={TREC},
year={2002}
}
```
| irds/gov_trec-web-2002_named-page | [
"task_categories:text-retrieval",
"source_datasets:irds/gov",
"region:us"
] | 2023-01-05T03:04:38+00:00 | {"source_datasets": ["irds/gov"], "task_categories": ["text-retrieval"], "pretty_name": "`gov/trec-web-2002/named-page`", "viewer": false} | 2023-01-05T03:04:44+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov #region-us
|
# Dataset Card for 'gov/trec-web-2002/named-page'
The 'gov/trec-web-2002/named-page' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=150
- 'qrels': (relevance assessments); count=170
- For 'docs', use 'irds/gov'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov/trec-web-2002/named-page'\n\nThe 'gov/trec-web-2002/named-page' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=150\n - 'qrels': (relevance assessments); count=170\n\n - For 'docs', use 'irds/gov'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov #region-us \n",
"# Dataset Card for 'gov/trec-web-2002/named-page'\n\nThe 'gov/trec-web-2002/named-page' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=150\n - 'qrels': (relevance assessments); count=170\n\n - For 'docs', use 'irds/gov'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
35a75500ca891fa8f537320972c1cfa5936682ba |
# Dataset Card for `gov/trec-web-2003`
The `gov/trec-web-2003` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov#gov/trec-web-2003).
# Data
This dataset provides:
- `queries` (i.e., topics); count=50
- `qrels`: (relevance assessments); count=51,062
- For `docs`, use [`irds/gov`](https://huggingface.co/datasets/irds/gov)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov_trec-web-2003', 'queries')
for record in queries:
record # {'query_id': ..., 'title': ..., 'description': ...}
qrels = load_dataset('irds/gov_trec-web-2003', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Craswell2003TrecWeb,
title={Overview of the TREC 2003 Web Track},
author={Nick Craswell and David Hawking and Ross Wilkinson and Mingfang Wu},
booktitle={TREC},
year={2003}
}
```
| irds/gov_trec-web-2003 | [
"task_categories:text-retrieval",
"source_datasets:irds/gov",
"region:us"
] | 2023-01-05T03:04:49+00:00 | {"source_datasets": ["irds/gov"], "task_categories": ["text-retrieval"], "pretty_name": "`gov/trec-web-2003`", "viewer": false} | 2023-01-05T03:04:55+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov #region-us
|
# Dataset Card for 'gov/trec-web-2003'
The 'gov/trec-web-2003' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=50
- 'qrels': (relevance assessments); count=51,062
- For 'docs', use 'irds/gov'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov/trec-web-2003'\n\nThe 'gov/trec-web-2003' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=50\n - 'qrels': (relevance assessments); count=51,062\n\n - For 'docs', use 'irds/gov'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov #region-us \n",
"# Dataset Card for 'gov/trec-web-2003'\n\nThe 'gov/trec-web-2003' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=50\n - 'qrels': (relevance assessments); count=51,062\n\n - For 'docs', use 'irds/gov'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
daf17aca06f2fbd03694fdbc0ad5d94d4fe53ff8 |
# Dataset Card for `gov/trec-web-2003/named-page`
The `gov/trec-web-2003/named-page` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov#gov/trec-web-2003/named-page).
# Data
This dataset provides:
- `queries` (i.e., topics); count=300
- `qrels`: (relevance assessments); count=352
- For `docs`, use [`irds/gov`](https://huggingface.co/datasets/irds/gov)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov_trec-web-2003_named-page', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/gov_trec-web-2003_named-page', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Craswell2003TrecWeb,
title={Overview of the TREC 2003 Web Track},
author={Nick Craswell and David Hawking and Ross Wilkinson and Mingfang Wu},
booktitle={TREC},
year={2003}
}
```
| irds/gov_trec-web-2003_named-page | [
"task_categories:text-retrieval",
"source_datasets:irds/gov",
"region:us"
] | 2023-01-05T03:05:01+00:00 | {"source_datasets": ["irds/gov"], "task_categories": ["text-retrieval"], "pretty_name": "`gov/trec-web-2003/named-page`", "viewer": false} | 2023-01-05T03:05:06+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov #region-us
|
# Dataset Card for 'gov/trec-web-2003/named-page'
The 'gov/trec-web-2003/named-page' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=300
- 'qrels': (relevance assessments); count=352
- For 'docs', use 'irds/gov'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov/trec-web-2003/named-page'\n\nThe 'gov/trec-web-2003/named-page' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=300\n - 'qrels': (relevance assessments); count=352\n\n - For 'docs', use 'irds/gov'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov #region-us \n",
"# Dataset Card for 'gov/trec-web-2003/named-page'\n\nThe 'gov/trec-web-2003/named-page' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=300\n - 'qrels': (relevance assessments); count=352\n\n - For 'docs', use 'irds/gov'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
d1352d159cb6c228181be05870570321b028abbe |
# Dataset Card for `gov/trec-web-2004`
The `gov/trec-web-2004` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov#gov/trec-web-2004).
# Data
This dataset provides:
- `queries` (i.e., topics); count=225
- `qrels`: (relevance assessments); count=88,566
- For `docs`, use [`irds/gov`](https://huggingface.co/datasets/irds/gov)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov_trec-web-2004', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/gov_trec-web-2004', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Craswell2004TrecWeb,
title={Overview of the TREC-2004 Web Track},
author={Nick Craswell and David Hawking},
booktitle={TREC},
year={2004}
}
```
| irds/gov_trec-web-2004 | [
"task_categories:text-retrieval",
"source_datasets:irds/gov",
"region:us"
] | 2023-01-05T03:05:12+00:00 | {"source_datasets": ["irds/gov"], "task_categories": ["text-retrieval"], "pretty_name": "`gov/trec-web-2004`", "viewer": false} | 2023-01-05T03:05:17+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov #region-us
|
# Dataset Card for 'gov/trec-web-2004'
The 'gov/trec-web-2004' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=225
- 'qrels': (relevance assessments); count=88,566
- For 'docs', use 'irds/gov'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov/trec-web-2004'\n\nThe 'gov/trec-web-2004' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=225\n - 'qrels': (relevance assessments); count=88,566\n\n - For 'docs', use 'irds/gov'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov #region-us \n",
"# Dataset Card for 'gov/trec-web-2004'\n\nThe 'gov/trec-web-2004' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=225\n - 'qrels': (relevance assessments); count=88,566\n\n - For 'docs', use 'irds/gov'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
a6e2d7fc839582490032cf2d4f3ae10161fd4beb |
# Dataset Card for `gov2`
The `gov2` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov2#gov2).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=25,205,179
This dataset is used by: [`gov2_trec-tb-2004`](https://huggingface.co/datasets/irds/gov2_trec-tb-2004), [`gov2_trec-tb-2005`](https://huggingface.co/datasets/irds/gov2_trec-tb-2005), [`gov2_trec-tb-2005_efficiency`](https://huggingface.co/datasets/irds/gov2_trec-tb-2005_efficiency), [`gov2_trec-tb-2005_named-page`](https://huggingface.co/datasets/irds/gov2_trec-tb-2005_named-page), [`gov2_trec-tb-2006`](https://huggingface.co/datasets/irds/gov2_trec-tb-2006), [`gov2_trec-tb-2006_efficiency`](https://huggingface.co/datasets/irds/gov2_trec-tb-2006_efficiency), [`gov2_trec-tb-2006_efficiency_10k`](https://huggingface.co/datasets/irds/gov2_trec-tb-2006_efficiency_10k), [`gov2_trec-tb-2006_efficiency_stream1`](https://huggingface.co/datasets/irds/gov2_trec-tb-2006_efficiency_stream1), [`gov2_trec-tb-2006_efficiency_stream2`](https://huggingface.co/datasets/irds/gov2_trec-tb-2006_efficiency_stream2), [`gov2_trec-tb-2006_efficiency_stream3`](https://huggingface.co/datasets/irds/gov2_trec-tb-2006_efficiency_stream3), [`gov2_trec-tb-2006_efficiency_stream4`](https://huggingface.co/datasets/irds/gov2_trec-tb-2006_efficiency_stream4), [`gov2_trec-tb-2006_named-page`](https://huggingface.co/datasets/irds/gov2_trec-tb-2006_named-page)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/gov2', 'docs')
for record in docs:
record # {'doc_id': ..., 'url': ..., 'http_headers': ..., 'body': ..., 'body_content_type': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
| irds/gov2 | [
"task_categories:text-retrieval",
"region:us"
] | 2023-01-05T03:05:23+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`gov2`", "viewer": false} | 2023-01-05T03:05:28+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #region-us
|
# Dataset Card for 'gov2'
The 'gov2' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=25,205,179
This dataset is used by: 'gov2_trec-tb-2004', 'gov2_trec-tb-2005', 'gov2_trec-tb-2005_efficiency', 'gov2_trec-tb-2005_named-page', 'gov2_trec-tb-2006', 'gov2_trec-tb-2006_efficiency', 'gov2_trec-tb-2006_efficiency_10k', 'gov2_trec-tb-2006_efficiency_stream1', 'gov2_trec-tb-2006_efficiency_stream2', 'gov2_trec-tb-2006_efficiency_stream3', 'gov2_trec-tb-2006_efficiency_stream4', 'gov2_trec-tb-2006_named-page'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov2'\n\nThe 'gov2' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=25,205,179\n\n\nThis dataset is used by: 'gov2_trec-tb-2004', 'gov2_trec-tb-2005', 'gov2_trec-tb-2005_efficiency', 'gov2_trec-tb-2005_named-page', 'gov2_trec-tb-2006', 'gov2_trec-tb-2006_efficiency', 'gov2_trec-tb-2006_efficiency_10k', 'gov2_trec-tb-2006_efficiency_stream1', 'gov2_trec-tb-2006_efficiency_stream2', 'gov2_trec-tb-2006_efficiency_stream3', 'gov2_trec-tb-2006_efficiency_stream4', 'gov2_trec-tb-2006_named-page'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #region-us \n",
"# Dataset Card for 'gov2'\n\nThe 'gov2' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=25,205,179\n\n\nThis dataset is used by: 'gov2_trec-tb-2004', 'gov2_trec-tb-2005', 'gov2_trec-tb-2005_efficiency', 'gov2_trec-tb-2005_named-page', 'gov2_trec-tb-2006', 'gov2_trec-tb-2006_efficiency', 'gov2_trec-tb-2006_efficiency_10k', 'gov2_trec-tb-2006_efficiency_stream1', 'gov2_trec-tb-2006_efficiency_stream2', 'gov2_trec-tb-2006_efficiency_stream3', 'gov2_trec-tb-2006_efficiency_stream4', 'gov2_trec-tb-2006_named-page'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
9afbbc7f7fe33a8317f1ffa590c7cb8822d47b43 |
# Dataset Card for `gov2/trec-tb-2004`
The `gov2/trec-tb-2004` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov2#gov2/trec-tb-2004).
# Data
This dataset provides:
- `queries` (i.e., topics); count=50
- `qrels`: (relevance assessments); count=58,077
- For `docs`, use [`irds/gov2`](https://huggingface.co/datasets/irds/gov2)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov2_trec-tb-2004', 'queries')
for record in queries:
record # {'query_id': ..., 'title': ..., 'description': ..., 'narrative': ...}
qrels = load_dataset('irds/gov2_trec-tb-2004', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Clarke2004TrecTerabyte,
title={Overview of the TREC 2004 Terabyte Track},
author={Charles Clarke and Nick Craswell and Ian Soboroff},
booktitle={TREC},
year={2004}
}
```
| irds/gov2_trec-tb-2004 | [
"task_categories:text-retrieval",
"source_datasets:irds/gov2",
"region:us"
] | 2023-01-05T03:05:34+00:00 | {"source_datasets": ["irds/gov2"], "task_categories": ["text-retrieval"], "pretty_name": "`gov2/trec-tb-2004`", "viewer": false} | 2023-01-05T03:05:40+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us
|
# Dataset Card for 'gov2/trec-tb-2004'
The 'gov2/trec-tb-2004' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=50
- 'qrels': (relevance assessments); count=58,077
- For 'docs', use 'irds/gov2'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov2/trec-tb-2004'\n\nThe 'gov2/trec-tb-2004' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=50\n - 'qrels': (relevance assessments); count=58,077\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us \n",
"# Dataset Card for 'gov2/trec-tb-2004'\n\nThe 'gov2/trec-tb-2004' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=50\n - 'qrels': (relevance assessments); count=58,077\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
ed007f5ae9e94b1ff6413897824f9f006648d38b |
# Dataset Card for `gov2/trec-tb-2005`
The `gov2/trec-tb-2005` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov2#gov2/trec-tb-2005).
# Data
This dataset provides:
- `queries` (i.e., topics); count=50
- `qrels`: (relevance assessments); count=45,291
- For `docs`, use [`irds/gov2`](https://huggingface.co/datasets/irds/gov2)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov2_trec-tb-2005', 'queries')
for record in queries:
record # {'query_id': ..., 'title': ..., 'description': ..., 'narrative': ...}
qrels = load_dataset('irds/gov2_trec-tb-2005', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Clarke2005TrecTerabyte,
title={The TREC 2005 Terabyte Track},
author={Charles L. A. Clark and Falk Scholer and Ian Soboroff},
booktitle={TREC},
year={2005}
}
```
| irds/gov2_trec-tb-2005 | [
"task_categories:text-retrieval",
"source_datasets:irds/gov2",
"region:us"
] | 2023-01-05T03:05:45+00:00 | {"source_datasets": ["irds/gov2"], "task_categories": ["text-retrieval"], "pretty_name": "`gov2/trec-tb-2005`", "viewer": false} | 2023-01-05T03:05:51+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us
|
# Dataset Card for 'gov2/trec-tb-2005'
The 'gov2/trec-tb-2005' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=50
- 'qrels': (relevance assessments); count=45,291
- For 'docs', use 'irds/gov2'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov2/trec-tb-2005'\n\nThe 'gov2/trec-tb-2005' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=50\n - 'qrels': (relevance assessments); count=45,291\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us \n",
"# Dataset Card for 'gov2/trec-tb-2005'\n\nThe 'gov2/trec-tb-2005' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=50\n - 'qrels': (relevance assessments); count=45,291\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
0c7faf9df24d33af823cfa8243e9315b67d9add6 |
# Dataset Card for `gov2/trec-tb-2005/efficiency`
The `gov2/trec-tb-2005/efficiency` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov2#gov2/trec-tb-2005/efficiency).
# Data
This dataset provides:
- `queries` (i.e., topics); count=50,000
- `qrels`: (relevance assessments); count=45,291
- For `docs`, use [`irds/gov2`](https://huggingface.co/datasets/irds/gov2)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov2_trec-tb-2005_efficiency', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/gov2_trec-tb-2005_efficiency', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Clarke2005TrecTerabyte,
title={The TREC 2005 Terabyte Track},
author={Charles L. A. Clark and Falk Scholer and Ian Soboroff},
booktitle={TREC},
year={2005}
}
```
| irds/gov2_trec-tb-2005_efficiency | [
"task_categories:text-retrieval",
"source_datasets:irds/gov2",
"region:us"
] | 2023-01-05T03:05:56+00:00 | {"source_datasets": ["irds/gov2"], "task_categories": ["text-retrieval"], "pretty_name": "`gov2/trec-tb-2005/efficiency`", "viewer": false} | 2023-01-05T03:06:02+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us
|
# Dataset Card for 'gov2/trec-tb-2005/efficiency'
The 'gov2/trec-tb-2005/efficiency' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=50,000
- 'qrels': (relevance assessments); count=45,291
- For 'docs', use 'irds/gov2'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov2/trec-tb-2005/efficiency'\n\nThe 'gov2/trec-tb-2005/efficiency' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=50,000\n - 'qrels': (relevance assessments); count=45,291\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us \n",
"# Dataset Card for 'gov2/trec-tb-2005/efficiency'\n\nThe 'gov2/trec-tb-2005/efficiency' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=50,000\n - 'qrels': (relevance assessments); count=45,291\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
cb1e910defebf5653c29c7d2f99871e81b982399 |
# Dataset Card for `gov2/trec-tb-2005/named-page`
The `gov2/trec-tb-2005/named-page` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov2#gov2/trec-tb-2005/named-page).
# Data
This dataset provides:
- `queries` (i.e., topics); count=252
- `qrels`: (relevance assessments); count=11,729
- For `docs`, use [`irds/gov2`](https://huggingface.co/datasets/irds/gov2)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov2_trec-tb-2005_named-page', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/gov2_trec-tb-2005_named-page', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Clarke2005TrecTerabyte,
title={The TREC 2005 Terabyte Track},
author={Charles L. A. Clark and Falk Scholer and Ian Soboroff},
booktitle={TREC},
year={2005}
}
```
| irds/gov2_trec-tb-2005_named-page | [
"task_categories:text-retrieval",
"source_datasets:irds/gov2",
"region:us"
] | 2023-01-05T03:06:07+00:00 | {"source_datasets": ["irds/gov2"], "task_categories": ["text-retrieval"], "pretty_name": "`gov2/trec-tb-2005/named-page`", "viewer": false} | 2023-01-05T03:06:13+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us
|
# Dataset Card for 'gov2/trec-tb-2005/named-page'
The 'gov2/trec-tb-2005/named-page' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=252
- 'qrels': (relevance assessments); count=11,729
- For 'docs', use 'irds/gov2'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov2/trec-tb-2005/named-page'\n\nThe 'gov2/trec-tb-2005/named-page' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=252\n - 'qrels': (relevance assessments); count=11,729\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us \n",
"# Dataset Card for 'gov2/trec-tb-2005/named-page'\n\nThe 'gov2/trec-tb-2005/named-page' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=252\n - 'qrels': (relevance assessments); count=11,729\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
41b52f39f0d0c1bcc7ad6523e93099129fc19e8b |
# Dataset Card for `gov2/trec-tb-2006`
The `gov2/trec-tb-2006` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov2#gov2/trec-tb-2006).
# Data
This dataset provides:
- `queries` (i.e., topics); count=50
- `qrels`: (relevance assessments); count=31,984
- For `docs`, use [`irds/gov2`](https://huggingface.co/datasets/irds/gov2)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov2_trec-tb-2006', 'queries')
for record in queries:
record # {'query_id': ..., 'title': ..., 'description': ..., 'narrative': ...}
qrels = load_dataset('irds/gov2_trec-tb-2006', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Buttcher2006TrecTerabyte,
title={The TREC 2006 Terabyte Track},
author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff},
booktitle={TREC},
year={2006}
}
```
| irds/gov2_trec-tb-2006 | [
"task_categories:text-retrieval",
"source_datasets:irds/gov2",
"region:us"
] | 2023-01-05T03:06:19+00:00 | {"source_datasets": ["irds/gov2"], "task_categories": ["text-retrieval"], "pretty_name": "`gov2/trec-tb-2006`", "viewer": false} | 2023-01-05T03:06:24+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us
|
# Dataset Card for 'gov2/trec-tb-2006'
The 'gov2/trec-tb-2006' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=50
- 'qrels': (relevance assessments); count=31,984
- For 'docs', use 'irds/gov2'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov2/trec-tb-2006'\n\nThe 'gov2/trec-tb-2006' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=50\n - 'qrels': (relevance assessments); count=31,984\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us \n",
"# Dataset Card for 'gov2/trec-tb-2006'\n\nThe 'gov2/trec-tb-2006' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=50\n - 'qrels': (relevance assessments); count=31,984\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
19243bade1eb835e274d190116b39e1530902d9d |
# Dataset Card for `gov2/trec-tb-2006/efficiency`
The `gov2/trec-tb-2006/efficiency` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov2#gov2/trec-tb-2006/efficiency).
# Data
This dataset provides:
- `queries` (i.e., topics); count=100,000
- `qrels`: (relevance assessments); count=31,984
- For `docs`, use [`irds/gov2`](https://huggingface.co/datasets/irds/gov2)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov2_trec-tb-2006_efficiency', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/gov2_trec-tb-2006_efficiency', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Buttcher2006TrecTerabyte,
title={The TREC 2006 Terabyte Track},
author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff},
booktitle={TREC},
year={2006}
}
```
| irds/gov2_trec-tb-2006_efficiency | [
"task_categories:text-retrieval",
"source_datasets:irds/gov2",
"region:us"
] | 2023-01-05T03:06:30+00:00 | {"source_datasets": ["irds/gov2"], "task_categories": ["text-retrieval"], "pretty_name": "`gov2/trec-tb-2006/efficiency`", "viewer": false} | 2023-01-05T03:06:35+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us
|
# Dataset Card for 'gov2/trec-tb-2006/efficiency'
The 'gov2/trec-tb-2006/efficiency' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=100,000
- 'qrels': (relevance assessments); count=31,984
- For 'docs', use 'irds/gov2'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov2/trec-tb-2006/efficiency'\n\nThe 'gov2/trec-tb-2006/efficiency' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=100,000\n - 'qrels': (relevance assessments); count=31,984\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us \n",
"# Dataset Card for 'gov2/trec-tb-2006/efficiency'\n\nThe 'gov2/trec-tb-2006/efficiency' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=100,000\n - 'qrels': (relevance assessments); count=31,984\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
e3d756ae76572fe72ae3892800e5e0a52990cede |
# Dataset Card for `gov2/trec-tb-2006/efficiency/10k`
The `gov2/trec-tb-2006/efficiency/10k` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov2#gov2/trec-tb-2006/efficiency/10k).
# Data
This dataset provides:
- `queries` (i.e., topics); count=10,000
- For `docs`, use [`irds/gov2`](https://huggingface.co/datasets/irds/gov2)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov2_trec-tb-2006_efficiency_10k', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Buttcher2006TrecTerabyte,
title={The TREC 2006 Terabyte Track},
author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff},
booktitle={TREC},
year={2006}
}
```
| irds/gov2_trec-tb-2006_efficiency_10k | [
"task_categories:text-retrieval",
"source_datasets:irds/gov2",
"region:us"
] | 2023-01-05T03:06:41+00:00 | {"source_datasets": ["irds/gov2"], "task_categories": ["text-retrieval"], "pretty_name": "`gov2/trec-tb-2006/efficiency/10k`", "viewer": false} | 2023-01-05T03:06:47+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us
|
# Dataset Card for 'gov2/trec-tb-2006/efficiency/10k'
The 'gov2/trec-tb-2006/efficiency/10k' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=10,000
- For 'docs', use 'irds/gov2'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov2/trec-tb-2006/efficiency/10k'\n\nThe 'gov2/trec-tb-2006/efficiency/10k' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10,000\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us \n",
"# Dataset Card for 'gov2/trec-tb-2006/efficiency/10k'\n\nThe 'gov2/trec-tb-2006/efficiency/10k' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10,000\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
fd52750a3f6be643229b03bd1e639f17cbf4e9cc |
# Dataset Card for `gov2/trec-tb-2006/efficiency/stream1`
The `gov2/trec-tb-2006/efficiency/stream1` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov2#gov2/trec-tb-2006/efficiency/stream1).
# Data
This dataset provides:
- `queries` (i.e., topics); count=25,000
- For `docs`, use [`irds/gov2`](https://huggingface.co/datasets/irds/gov2)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov2_trec-tb-2006_efficiency_stream1', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Buttcher2006TrecTerabyte,
title={The TREC 2006 Terabyte Track},
author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff},
booktitle={TREC},
year={2006}
}
```
| irds/gov2_trec-tb-2006_efficiency_stream1 | [
"task_categories:text-retrieval",
"source_datasets:irds/gov2",
"region:us"
] | 2023-01-05T03:06:52+00:00 | {"source_datasets": ["irds/gov2"], "task_categories": ["text-retrieval"], "pretty_name": "`gov2/trec-tb-2006/efficiency/stream1`", "viewer": false} | 2023-01-05T03:06:58+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us
|
# Dataset Card for 'gov2/trec-tb-2006/efficiency/stream1'
The 'gov2/trec-tb-2006/efficiency/stream1' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=25,000
- For 'docs', use 'irds/gov2'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov2/trec-tb-2006/efficiency/stream1'\n\nThe 'gov2/trec-tb-2006/efficiency/stream1' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=25,000\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us \n",
"# Dataset Card for 'gov2/trec-tb-2006/efficiency/stream1'\n\nThe 'gov2/trec-tb-2006/efficiency/stream1' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=25,000\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
3e3164cff2535e08413aaf0176ef560864c138bf |
# Dataset Card for `gov2/trec-tb-2006/efficiency/stream2`
The `gov2/trec-tb-2006/efficiency/stream2` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov2#gov2/trec-tb-2006/efficiency/stream2).
# Data
This dataset provides:
- `queries` (i.e., topics); count=25,000
- For `docs`, use [`irds/gov2`](https://huggingface.co/datasets/irds/gov2)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov2_trec-tb-2006_efficiency_stream2', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Buttcher2006TrecTerabyte,
title={The TREC 2006 Terabyte Track},
author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff},
booktitle={TREC},
year={2006}
}
```
| irds/gov2_trec-tb-2006_efficiency_stream2 | [
"task_categories:text-retrieval",
"source_datasets:irds/gov2",
"region:us"
] | 2023-01-05T03:07:03+00:00 | {"source_datasets": ["irds/gov2"], "task_categories": ["text-retrieval"], "pretty_name": "`gov2/trec-tb-2006/efficiency/stream2`", "viewer": false} | 2023-01-05T03:07:09+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us
|
# Dataset Card for 'gov2/trec-tb-2006/efficiency/stream2'
The 'gov2/trec-tb-2006/efficiency/stream2' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=25,000
- For 'docs', use 'irds/gov2'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov2/trec-tb-2006/efficiency/stream2'\n\nThe 'gov2/trec-tb-2006/efficiency/stream2' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=25,000\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us \n",
"# Dataset Card for 'gov2/trec-tb-2006/efficiency/stream2'\n\nThe 'gov2/trec-tb-2006/efficiency/stream2' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=25,000\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
2abe54278e42abfb1eed006b2762636d4b9e50e4 |
# Dataset Card for `gov2/trec-tb-2006/efficiency/stream3`
The `gov2/trec-tb-2006/efficiency/stream3` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov2#gov2/trec-tb-2006/efficiency/stream3).
# Data
This dataset provides:
- `queries` (i.e., topics); count=25,000
- `qrels`: (relevance assessments); count=31,984
- For `docs`, use [`irds/gov2`](https://huggingface.co/datasets/irds/gov2)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov2_trec-tb-2006_efficiency_stream3', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/gov2_trec-tb-2006_efficiency_stream3', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Buttcher2006TrecTerabyte,
title={The TREC 2006 Terabyte Track},
author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff},
booktitle={TREC},
year={2006}
}
```
| irds/gov2_trec-tb-2006_efficiency_stream3 | [
"task_categories:text-retrieval",
"source_datasets:irds/gov2",
"region:us"
] | 2023-01-05T03:07:14+00:00 | {"source_datasets": ["irds/gov2"], "task_categories": ["text-retrieval"], "pretty_name": "`gov2/trec-tb-2006/efficiency/stream3`", "viewer": false} | 2023-01-05T03:07:20+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us
|
# Dataset Card for 'gov2/trec-tb-2006/efficiency/stream3'
The 'gov2/trec-tb-2006/efficiency/stream3' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=25,000
- 'qrels': (relevance assessments); count=31,984
- For 'docs', use 'irds/gov2'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov2/trec-tb-2006/efficiency/stream3'\n\nThe 'gov2/trec-tb-2006/efficiency/stream3' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=25,000\n - 'qrels': (relevance assessments); count=31,984\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us \n",
"# Dataset Card for 'gov2/trec-tb-2006/efficiency/stream3'\n\nThe 'gov2/trec-tb-2006/efficiency/stream3' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=25,000\n - 'qrels': (relevance assessments); count=31,984\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
2fa71fc9278da58fb24782a6d2f45fcb08aca99a |
# Dataset Card for `gov2/trec-tb-2006/efficiency/stream4`
The `gov2/trec-tb-2006/efficiency/stream4` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov2#gov2/trec-tb-2006/efficiency/stream4).
# Data
This dataset provides:
- `queries` (i.e., topics); count=25,000
- For `docs`, use [`irds/gov2`](https://huggingface.co/datasets/irds/gov2)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov2_trec-tb-2006_efficiency_stream4', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Buttcher2006TrecTerabyte,
title={The TREC 2006 Terabyte Track},
author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff},
booktitle={TREC},
year={2006}
}
```
| irds/gov2_trec-tb-2006_efficiency_stream4 | [
"task_categories:text-retrieval",
"source_datasets:irds/gov2",
"region:us"
] | 2023-01-05T03:07:26+00:00 | {"source_datasets": ["irds/gov2"], "task_categories": ["text-retrieval"], "pretty_name": "`gov2/trec-tb-2006/efficiency/stream4`", "viewer": false} | 2023-01-05T03:07:31+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us
|
# Dataset Card for 'gov2/trec-tb-2006/efficiency/stream4'
The 'gov2/trec-tb-2006/efficiency/stream4' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=25,000
- For 'docs', use 'irds/gov2'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov2/trec-tb-2006/efficiency/stream4'\n\nThe 'gov2/trec-tb-2006/efficiency/stream4' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=25,000\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us \n",
"# Dataset Card for 'gov2/trec-tb-2006/efficiency/stream4'\n\nThe 'gov2/trec-tb-2006/efficiency/stream4' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=25,000\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
fe821b56dfd5271b0dfa32f13ed7336929e5a9cc |
# Dataset Card for `gov2/trec-tb-2006/named-page`
The `gov2/trec-tb-2006/named-page` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/gov2#gov2/trec-tb-2006/named-page).
# Data
This dataset provides:
- `queries` (i.e., topics); count=181
- `qrels`: (relevance assessments); count=2,361
- For `docs`, use [`irds/gov2`](https://huggingface.co/datasets/irds/gov2)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/gov2_trec-tb-2006_named-page', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/gov2_trec-tb-2006_named-page', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Buttcher2006TrecTerabyte,
title={The TREC 2006 Terabyte Track},
author={Stefan B\"uttcher and Charles L. A. Clarke and Ian Soboroff},
booktitle={TREC},
year={2006}
}
```
| irds/gov2_trec-tb-2006_named-page | [
"task_categories:text-retrieval",
"source_datasets:irds/gov2",
"region:us"
] | 2023-01-05T03:07:37+00:00 | {"source_datasets": ["irds/gov2"], "task_categories": ["text-retrieval"], "pretty_name": "`gov2/trec-tb-2006/named-page`", "viewer": false} | 2023-01-05T03:07:43+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us
|
# Dataset Card for 'gov2/trec-tb-2006/named-page'
The 'gov2/trec-tb-2006/named-page' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=181
- 'qrels': (relevance assessments); count=2,361
- For 'docs', use 'irds/gov2'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'gov2/trec-tb-2006/named-page'\n\nThe 'gov2/trec-tb-2006/named-page' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=181\n - 'qrels': (relevance assessments); count=2,361\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/gov2 #region-us \n",
"# Dataset Card for 'gov2/trec-tb-2006/named-page'\n\nThe 'gov2/trec-tb-2006/named-page' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=181\n - 'qrels': (relevance assessments); count=2,361\n\n - For 'docs', use 'irds/gov2'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
f6394b2a7d0fdf89462ab4fa26ca909543e89647 |
# Dataset Card for `istella22`
The `istella22` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/istella22#istella22).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=8,421,456
This dataset is used by: [`istella22_test`](https://huggingface.co/datasets/irds/istella22_test), [`istella22_test_fold1`](https://huggingface.co/datasets/irds/istella22_test_fold1), [`istella22_test_fold2`](https://huggingface.co/datasets/irds/istella22_test_fold2), [`istella22_test_fold3`](https://huggingface.co/datasets/irds/istella22_test_fold3), [`istella22_test_fold4`](https://huggingface.co/datasets/irds/istella22_test_fold4), [`istella22_test_fold5`](https://huggingface.co/datasets/irds/istella22_test_fold5)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/istella22', 'docs')
for record in docs:
record # {'doc_id': ..., 'title': ..., 'url': ..., 'text': ..., 'extra_text': ..., 'lang': ..., 'lang_pct': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Dato2022Istella,
title={The Istella22 Dataset: Bridging Traditional and Neural Learning to Rank Evaluation},
author={Domenico Dato, Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto},
booktitle={Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval},
year={2022}
}
```
| irds/istella22 | [
"task_categories:text-retrieval",
"region:us"
] | 2023-01-05T03:07:48+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`istella22`", "viewer": false} | 2023-01-05T03:07:54+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #region-us
|
# Dataset Card for 'istella22'
The 'istella22' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=8,421,456
This dataset is used by: 'istella22_test', 'istella22_test_fold1', 'istella22_test_fold2', 'istella22_test_fold3', 'istella22_test_fold4', 'istella22_test_fold5'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'istella22'\n\nThe 'istella22' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,421,456\n\n\nThis dataset is used by: 'istella22_test', 'istella22_test_fold1', 'istella22_test_fold2', 'istella22_test_fold3', 'istella22_test_fold4', 'istella22_test_fold5'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #region-us \n",
"# Dataset Card for 'istella22'\n\nThe 'istella22' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,421,456\n\n\nThis dataset is used by: 'istella22_test', 'istella22_test_fold1', 'istella22_test_fold2', 'istella22_test_fold3', 'istella22_test_fold4', 'istella22_test_fold5'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
1d99a336dad14d72c13df9cb7d5e3c4ef410be80 |
# Dataset Card for `istella22/test`
The `istella22/test` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/istella22#istella22/test).
# Data
This dataset provides:
- `queries` (i.e., topics); count=2,198
- `qrels`: (relevance assessments); count=10,693
- For `docs`, use [`irds/istella22`](https://huggingface.co/datasets/irds/istella22)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/istella22_test', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/istella22_test', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
| irds/istella22_test | [
"task_categories:text-retrieval",
"source_datasets:irds/istella22",
"region:us"
] | 2023-01-05T03:07:59+00:00 | {"source_datasets": ["irds/istella22"], "task_categories": ["text-retrieval"], "pretty_name": "`istella22/test`", "viewer": false} | 2023-01-05T03:08:05+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/istella22 #region-us
|
# Dataset Card for 'istella22/test'
The 'istella22/test' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=2,198
- 'qrels': (relevance assessments); count=10,693
- For 'docs', use 'irds/istella22'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'istella22/test'\n\nThe 'istella22/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,198\n - 'qrels': (relevance assessments); count=10,693\n\n - For 'docs', use 'irds/istella22'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/istella22 #region-us \n",
"# Dataset Card for 'istella22/test'\n\nThe 'istella22/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,198\n - 'qrels': (relevance assessments); count=10,693\n\n - For 'docs', use 'irds/istella22'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
9fc16f431ab78b78285726b01aec91953f01dbc3 |
# Dataset Card for `istella22/test/fold1`
The `istella22/test/fold1` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/istella22#istella22/test/fold1).
# Data
This dataset provides:
- `queries` (i.e., topics); count=440
- `qrels`: (relevance assessments); count=2,164
- For `docs`, use [`irds/istella22`](https://huggingface.co/datasets/irds/istella22)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/istella22_test_fold1', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/istella22_test_fold1', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
| irds/istella22_test_fold1 | [
"task_categories:text-retrieval",
"source_datasets:irds/istella22",
"region:us"
] | 2023-01-05T03:08:10+00:00 | {"source_datasets": ["irds/istella22"], "task_categories": ["text-retrieval"], "pretty_name": "`istella22/test/fold1`", "viewer": false} | 2023-01-05T03:08:18+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/istella22 #region-us
|
# Dataset Card for 'istella22/test/fold1'
The 'istella22/test/fold1' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=440
- 'qrels': (relevance assessments); count=2,164
- For 'docs', use 'irds/istella22'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'istella22/test/fold1'\n\nThe 'istella22/test/fold1' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=440\n - 'qrels': (relevance assessments); count=2,164\n\n - For 'docs', use 'irds/istella22'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/istella22 #region-us \n",
"# Dataset Card for 'istella22/test/fold1'\n\nThe 'istella22/test/fold1' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=440\n - 'qrels': (relevance assessments); count=2,164\n\n - For 'docs', use 'irds/istella22'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
fbac99676c8676cf704f3bfb9f783ade1bb6b8ee |
# Dataset Card for `istella22/test/fold2`
The `istella22/test/fold2` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/istella22#istella22/test/fold2).
# Data
This dataset provides:
- `queries` (i.e., topics); count=440
- `qrels`: (relevance assessments); count=2,140
- For `docs`, use [`irds/istella22`](https://huggingface.co/datasets/irds/istella22)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/istella22_test_fold2', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/istella22_test_fold2', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
| irds/istella22_test_fold2 | [
"task_categories:text-retrieval",
"source_datasets:irds/istella22",
"region:us"
] | 2023-01-05T03:08:23+00:00 | {"source_datasets": ["irds/istella22"], "task_categories": ["text-retrieval"], "pretty_name": "`istella22/test/fold2`", "viewer": false} | 2023-01-05T03:08:29+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/istella22 #region-us
|
# Dataset Card for 'istella22/test/fold2'
The 'istella22/test/fold2' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=440
- 'qrels': (relevance assessments); count=2,140
- For 'docs', use 'irds/istella22'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'istella22/test/fold2'\n\nThe 'istella22/test/fold2' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=440\n - 'qrels': (relevance assessments); count=2,140\n\n - For 'docs', use 'irds/istella22'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/istella22 #region-us \n",
"# Dataset Card for 'istella22/test/fold2'\n\nThe 'istella22/test/fold2' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=440\n - 'qrels': (relevance assessments); count=2,140\n\n - For 'docs', use 'irds/istella22'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
5d9c994c889eef5ccb629632d91a8559ae72bf8d |
# Dataset Card for `istella22/test/fold3`
The `istella22/test/fold3` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/istella22#istella22/test/fold3).
# Data
This dataset provides:
- `queries` (i.e., topics); count=440
- `qrels`: (relevance assessments); count=2,197
- For `docs`, use [`irds/istella22`](https://huggingface.co/datasets/irds/istella22)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/istella22_test_fold3', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/istella22_test_fold3', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
| irds/istella22_test_fold3 | [
"task_categories:text-retrieval",
"source_datasets:irds/istella22",
"region:us"
] | 2023-01-05T03:08:34+00:00 | {"source_datasets": ["irds/istella22"], "task_categories": ["text-retrieval"], "pretty_name": "`istella22/test/fold3`", "viewer": false} | 2023-01-05T03:08:40+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/istella22 #region-us
|
# Dataset Card for 'istella22/test/fold3'
The 'istella22/test/fold3' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=440
- 'qrels': (relevance assessments); count=2,197
- For 'docs', use 'irds/istella22'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'istella22/test/fold3'\n\nThe 'istella22/test/fold3' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=440\n - 'qrels': (relevance assessments); count=2,197\n\n - For 'docs', use 'irds/istella22'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/istella22 #region-us \n",
"# Dataset Card for 'istella22/test/fold3'\n\nThe 'istella22/test/fold3' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=440\n - 'qrels': (relevance assessments); count=2,197\n\n - For 'docs', use 'irds/istella22'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
78bdf9e0e6c3326cd5275c28ce7a301bd969d566 |
# Dataset Card for `istella22/test/fold4`
The `istella22/test/fold4` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/istella22#istella22/test/fold4).
# Data
This dataset provides:
- `queries` (i.e., topics); count=439
- `qrels`: (relevance assessments); count=2,098
- For `docs`, use [`irds/istella22`](https://huggingface.co/datasets/irds/istella22)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/istella22_test_fold4', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/istella22_test_fold4', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
| irds/istella22_test_fold4 | [
"task_categories:text-retrieval",
"source_datasets:irds/istella22",
"region:us"
] | 2023-01-05T03:08:45+00:00 | {"source_datasets": ["irds/istella22"], "task_categories": ["text-retrieval"], "pretty_name": "`istella22/test/fold4`", "viewer": false} | 2023-01-05T03:08:51+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/istella22 #region-us
|
# Dataset Card for 'istella22/test/fold4'
The 'istella22/test/fold4' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=439
- 'qrels': (relevance assessments); count=2,098
- For 'docs', use 'irds/istella22'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'istella22/test/fold4'\n\nThe 'istella22/test/fold4' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=439\n - 'qrels': (relevance assessments); count=2,098\n\n - For 'docs', use 'irds/istella22'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/istella22 #region-us \n",
"# Dataset Card for 'istella22/test/fold4'\n\nThe 'istella22/test/fold4' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=439\n - 'qrels': (relevance assessments); count=2,098\n\n - For 'docs', use 'irds/istella22'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
f19766cf5aaccbfd9ca38eb5f7914e0349fb8e76 |
# Dataset Card for `istella22/test/fold5`
The `istella22/test/fold5` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/istella22#istella22/test/fold5).
# Data
This dataset provides:
- `queries` (i.e., topics); count=439
- `qrels`: (relevance assessments); count=2,094
- For `docs`, use [`irds/istella22`](https://huggingface.co/datasets/irds/istella22)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/istella22_test_fold5', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/istella22_test_fold5', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
| irds/istella22_test_fold5 | [
"task_categories:text-retrieval",
"source_datasets:irds/istella22",
"region:us"
] | 2023-01-05T03:08:57+00:00 | {"source_datasets": ["irds/istella22"], "task_categories": ["text-retrieval"], "pretty_name": "`istella22/test/fold5`", "viewer": false} | 2023-01-05T03:09:02+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/istella22 #region-us
|
# Dataset Card for 'istella22/test/fold5'
The 'istella22/test/fold5' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=439
- 'qrels': (relevance assessments); count=2,094
- For 'docs', use 'irds/istella22'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'istella22/test/fold5'\n\nThe 'istella22/test/fold5' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=439\n - 'qrels': (relevance assessments); count=2,094\n\n - For 'docs', use 'irds/istella22'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/istella22 #region-us \n",
"# Dataset Card for 'istella22/test/fold5'\n\nThe 'istella22/test/fold5' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=439\n - 'qrels': (relevance assessments); count=2,094\n\n - For 'docs', use 'irds/istella22'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
4b138571b1401911836b428a82441d66f95019f6 |
# Dataset Card for `kilt/codec`
The `kilt/codec` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/kilt#kilt/codec).
# Data
This dataset provides:
- `queries` (i.e., topics); count=42
- `qrels`: (relevance assessments); count=11,323
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/kilt_codec', 'queries')
for record in queries:
record # {'query_id': ..., 'query': ..., 'domain': ..., 'guidelines': ...}
qrels = load_dataset('irds/kilt_codec', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{mackie2022codec,
title={CODEC: Complex Document and Entity Collection},
author={Mackie, Iain and Owoicho, Paul and Gemmell, Carlos and Fischer, Sophie and MacAvaney, Sean and Dalton, Jeffery},
booktitle={Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval},
year={2022}
}
```
| irds/kilt_codec | [
"task_categories:text-retrieval",
"region:us"
] | 2023-01-05T03:09:08+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`kilt/codec`", "viewer": false} | 2023-01-05T03:09:13+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #region-us
|
# Dataset Card for 'kilt/codec'
The 'kilt/codec' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=42
- 'qrels': (relevance assessments); count=11,323
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'kilt/codec'\n\nThe 'kilt/codec' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=42\n - 'qrels': (relevance assessments); count=11,323",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #region-us \n",
"# Dataset Card for 'kilt/codec'\n\nThe 'kilt/codec' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=42\n - 'qrels': (relevance assessments); count=11,323",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
c8bf6a2a6f8154011fafc511f01ebde3ddc1b175 |
# Dataset Card for `kilt/codec/economics`
The `kilt/codec/economics` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/kilt#kilt/codec/economics).
# Data
This dataset provides:
- `queries` (i.e., topics); count=14
- `qrels`: (relevance assessments); count=1,970
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/kilt_codec_economics', 'queries')
for record in queries:
record # {'query_id': ..., 'query': ..., 'domain': ..., 'guidelines': ...}
qrels = load_dataset('irds/kilt_codec_economics', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{mackie2022codec,
title={CODEC: Complex Document and Entity Collection},
author={Mackie, Iain and Owoicho, Paul and Gemmell, Carlos and Fischer, Sophie and MacAvaney, Sean and Dalton, Jeffery},
booktitle={Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval},
year={2022}
}
```
| irds/kilt_codec_economics | [
"task_categories:text-retrieval",
"region:us"
] | 2023-01-05T03:09:19+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`kilt/codec/economics`", "viewer": false} | 2023-01-05T03:09:25+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #region-us
|
# Dataset Card for 'kilt/codec/economics'
The 'kilt/codec/economics' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=14
- 'qrels': (relevance assessments); count=1,970
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'kilt/codec/economics'\n\nThe 'kilt/codec/economics' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=14\n - 'qrels': (relevance assessments); count=1,970",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #region-us \n",
"# Dataset Card for 'kilt/codec/economics'\n\nThe 'kilt/codec/economics' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=14\n - 'qrels': (relevance assessments); count=1,970",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
6eb7b3780a1f1fa18250eab2203f49e0b42ae1f0 |
# Dataset Card for `kilt/codec/history`
The `kilt/codec/history` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/kilt#kilt/codec/history).
# Data
This dataset provides:
- `queries` (i.e., topics); count=14
- `qrels`: (relevance assessments); count=2,024
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/kilt_codec_history', 'queries')
for record in queries:
record # {'query_id': ..., 'query': ..., 'domain': ..., 'guidelines': ...}
qrels = load_dataset('irds/kilt_codec_history', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{mackie2022codec,
title={CODEC: Complex Document and Entity Collection},
author={Mackie, Iain and Owoicho, Paul and Gemmell, Carlos and Fischer, Sophie and MacAvaney, Sean and Dalton, Jeffery},
booktitle={Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval},
year={2022}
}
```
| irds/kilt_codec_history | [
"task_categories:text-retrieval",
"region:us"
] | 2023-01-05T03:09:30+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`kilt/codec/history`", "viewer": false} | 2023-01-05T03:09:36+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #region-us
|
# Dataset Card for 'kilt/codec/history'
The 'kilt/codec/history' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=14
- 'qrels': (relevance assessments); count=2,024
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'kilt/codec/history'\n\nThe 'kilt/codec/history' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=14\n - 'qrels': (relevance assessments); count=2,024",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #region-us \n",
"# Dataset Card for 'kilt/codec/history'\n\nThe 'kilt/codec/history' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=14\n - 'qrels': (relevance assessments); count=2,024",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
148a3ea35e68f11b2e4e47c879cc4aad0fc4aa9e |
# Dataset Card for `kilt/codec/politics`
The `kilt/codec/politics` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/kilt#kilt/codec/politics).
# Data
This dataset provides:
- `queries` (i.e., topics); count=14
- `qrels`: (relevance assessments); count=2,192
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/kilt_codec_politics', 'queries')
for record in queries:
record # {'query_id': ..., 'query': ..., 'domain': ..., 'guidelines': ...}
qrels = load_dataset('irds/kilt_codec_politics', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{mackie2022codec,
title={CODEC: Complex Document and Entity Collection},
author={Mackie, Iain and Owoicho, Paul and Gemmell, Carlos and Fischer, Sophie and MacAvaney, Sean and Dalton, Jeffery},
booktitle={Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval},
year={2022}
}
```
| irds/kilt_codec_politics | [
"task_categories:text-retrieval",
"region:us"
] | 2023-01-05T03:09:41+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`kilt/codec/politics`", "viewer": false} | 2023-01-05T03:09:47+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #region-us
|
# Dataset Card for 'kilt/codec/politics'
The 'kilt/codec/politics' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=14
- 'qrels': (relevance assessments); count=2,192
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'kilt/codec/politics'\n\nThe 'kilt/codec/politics' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=14\n - 'qrels': (relevance assessments); count=2,192",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #region-us \n",
"# Dataset Card for 'kilt/codec/politics'\n\nThe 'kilt/codec/politics' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=14\n - 'qrels': (relevance assessments); count=2,192",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
8d45e5f830cd9fc636096112f75810cd36e98d2c |
# Dataset Card for `lotte/lifestyle/dev`
The `lotte/lifestyle/dev` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/lifestyle/dev).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=268,893
This dataset is used by: [`lotte_lifestyle_dev_forum`](https://huggingface.co/datasets/irds/lotte_lifestyle_dev_forum), [`lotte_lifestyle_dev_search`](https://huggingface.co/datasets/irds/lotte_lifestyle_dev_search)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/lotte_lifestyle_dev', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_lifestyle_dev | [
"task_categories:text-retrieval",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:09:52+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/lifestyle/dev`", "viewer": false} | 2023-01-05T03:09:58+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/lifestyle/dev'
The 'lotte/lifestyle/dev' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=268,893
This dataset is used by: 'lotte_lifestyle_dev_forum', 'lotte_lifestyle_dev_search'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/lifestyle/dev'\n\nThe 'lotte/lifestyle/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=268,893\n\n\nThis dataset is used by: 'lotte_lifestyle_dev_forum', 'lotte_lifestyle_dev_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/lifestyle/dev'\n\nThe 'lotte/lifestyle/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=268,893\n\n\nThis dataset is used by: 'lotte_lifestyle_dev_forum', 'lotte_lifestyle_dev_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
0bde24be728cf96f9f3fe015eff26bf55b4567bb |
# Dataset Card for `lotte/lifestyle/dev/forum`
The `lotte/lifestyle/dev/forum` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/lifestyle/dev/forum).
# Data
This dataset provides:
- `queries` (i.e., topics); count=2,076
- `qrels`: (relevance assessments); count=12,823
- For `docs`, use [`irds/lotte_lifestyle_dev`](https://huggingface.co/datasets/irds/lotte_lifestyle_dev)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_lifestyle_dev_forum', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_lifestyle_dev_forum', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_lifestyle_dev_forum | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_lifestyle_dev",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:10:04+00:00 | {"source_datasets": ["irds/lotte_lifestyle_dev"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/lifestyle/dev/forum`", "viewer": false} | 2023-01-05T03:10:09+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_lifestyle_dev #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/lifestyle/dev/forum'
The 'lotte/lifestyle/dev/forum' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=2,076
- 'qrels': (relevance assessments); count=12,823
- For 'docs', use 'irds/lotte_lifestyle_dev'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/lifestyle/dev/forum'\n\nThe 'lotte/lifestyle/dev/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,076\n - 'qrels': (relevance assessments); count=12,823\n\n - For 'docs', use 'irds/lotte_lifestyle_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_lifestyle_dev #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/lifestyle/dev/forum'\n\nThe 'lotte/lifestyle/dev/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,076\n - 'qrels': (relevance assessments); count=12,823\n\n - For 'docs', use 'irds/lotte_lifestyle_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
0d09b2703d15e805c03c5dce1a589b3329d1d9d4 |
# Dataset Card for `lotte/lifestyle/dev/search`
The `lotte/lifestyle/dev/search` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/lifestyle/dev/search).
# Data
This dataset provides:
- `queries` (i.e., topics); count=417
- `qrels`: (relevance assessments); count=1,376
- For `docs`, use [`irds/lotte_lifestyle_dev`](https://huggingface.co/datasets/irds/lotte_lifestyle_dev)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_lifestyle_dev_search', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_lifestyle_dev_search', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_lifestyle_dev_search | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_lifestyle_dev",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:10:15+00:00 | {"source_datasets": ["irds/lotte_lifestyle_dev"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/lifestyle/dev/search`", "viewer": false} | 2023-01-05T03:10:21+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_lifestyle_dev #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/lifestyle/dev/search'
The 'lotte/lifestyle/dev/search' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=417
- 'qrels': (relevance assessments); count=1,376
- For 'docs', use 'irds/lotte_lifestyle_dev'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/lifestyle/dev/search'\n\nThe 'lotte/lifestyle/dev/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=417\n - 'qrels': (relevance assessments); count=1,376\n\n - For 'docs', use 'irds/lotte_lifestyle_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_lifestyle_dev #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/lifestyle/dev/search'\n\nThe 'lotte/lifestyle/dev/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=417\n - 'qrels': (relevance assessments); count=1,376\n\n - For 'docs', use 'irds/lotte_lifestyle_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
b2c5c2e7b956f0d0af5eca72717f3375d8b5bbf8 |
# Dataset Card for `lotte/lifestyle/test`
The `lotte/lifestyle/test` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/lifestyle/test).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=119,461
This dataset is used by: [`lotte_lifestyle_test_forum`](https://huggingface.co/datasets/irds/lotte_lifestyle_test_forum), [`lotte_lifestyle_test_search`](https://huggingface.co/datasets/irds/lotte_lifestyle_test_search)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/lotte_lifestyle_test', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_lifestyle_test | [
"task_categories:text-retrieval",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:10:26+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/lifestyle/test`", "viewer": false} | 2023-01-05T03:10:32+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/lifestyle/test'
The 'lotte/lifestyle/test' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=119,461
This dataset is used by: 'lotte_lifestyle_test_forum', 'lotte_lifestyle_test_search'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/lifestyle/test'\n\nThe 'lotte/lifestyle/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=119,461\n\n\nThis dataset is used by: 'lotte_lifestyle_test_forum', 'lotte_lifestyle_test_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/lifestyle/test'\n\nThe 'lotte/lifestyle/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=119,461\n\n\nThis dataset is used by: 'lotte_lifestyle_test_forum', 'lotte_lifestyle_test_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
6fcb1bd0505f734da8f2b638297338b57bd1ad49 |
# Dataset Card for `lotte/lifestyle/test/forum`
The `lotte/lifestyle/test/forum` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/lifestyle/test/forum).
# Data
This dataset provides:
- `queries` (i.e., topics); count=2,002
- `qrels`: (relevance assessments); count=10,278
- For `docs`, use [`irds/lotte_lifestyle_test`](https://huggingface.co/datasets/irds/lotte_lifestyle_test)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_lifestyle_test_forum', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_lifestyle_test_forum', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_lifestyle_test_forum | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_lifestyle_test",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:10:38+00:00 | {"source_datasets": ["irds/lotte_lifestyle_test"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/lifestyle/test/forum`", "viewer": false} | 2023-01-05T03:10:45+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_lifestyle_test #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/lifestyle/test/forum'
The 'lotte/lifestyle/test/forum' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=2,002
- 'qrels': (relevance assessments); count=10,278
- For 'docs', use 'irds/lotte_lifestyle_test'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/lifestyle/test/forum'\n\nThe 'lotte/lifestyle/test/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,002\n - 'qrels': (relevance assessments); count=10,278\n\n - For 'docs', use 'irds/lotte_lifestyle_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_lifestyle_test #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/lifestyle/test/forum'\n\nThe 'lotte/lifestyle/test/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,002\n - 'qrels': (relevance assessments); count=10,278\n\n - For 'docs', use 'irds/lotte_lifestyle_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
d4624d3500a39c861da3a99bc0e59ab332ec03da |
# Dataset Card for `lotte/lifestyle/test/search`
The `lotte/lifestyle/test/search` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/lifestyle/test/search).
# Data
This dataset provides:
- `queries` (i.e., topics); count=661
- `qrels`: (relevance assessments); count=1,804
- For `docs`, use [`irds/lotte_lifestyle_test`](https://huggingface.co/datasets/irds/lotte_lifestyle_test)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_lifestyle_test_search', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_lifestyle_test_search', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_lifestyle_test_search | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_lifestyle_test",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:10:51+00:00 | {"source_datasets": ["irds/lotte_lifestyle_test"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/lifestyle/test/search`", "viewer": false} | 2023-01-05T03:10:56+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_lifestyle_test #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/lifestyle/test/search'
The 'lotte/lifestyle/test/search' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=661
- 'qrels': (relevance assessments); count=1,804
- For 'docs', use 'irds/lotte_lifestyle_test'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/lifestyle/test/search'\n\nThe 'lotte/lifestyle/test/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=661\n - 'qrels': (relevance assessments); count=1,804\n\n - For 'docs', use 'irds/lotte_lifestyle_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_lifestyle_test #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/lifestyle/test/search'\n\nThe 'lotte/lifestyle/test/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=661\n - 'qrels': (relevance assessments); count=1,804\n\n - For 'docs', use 'irds/lotte_lifestyle_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
386a3c998811da2c3e1be0a26eeccc4f8501b047 |
# Dataset Card for `lotte/pooled/dev`
The `lotte/pooled/dev` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/pooled/dev).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=2,428,854
This dataset is used by: [`lotte_pooled_dev_forum`](https://huggingface.co/datasets/irds/lotte_pooled_dev_forum), [`lotte_pooled_dev_search`](https://huggingface.co/datasets/irds/lotte_pooled_dev_search)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/lotte_pooled_dev', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_pooled_dev | [
"task_categories:text-retrieval",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:11:02+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/pooled/dev`", "viewer": false} | 2023-01-05T03:11:08+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/pooled/dev'
The 'lotte/pooled/dev' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=2,428,854
This dataset is used by: 'lotte_pooled_dev_forum', 'lotte_pooled_dev_search'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/pooled/dev'\n\nThe 'lotte/pooled/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=2,428,854\n\n\nThis dataset is used by: 'lotte_pooled_dev_forum', 'lotte_pooled_dev_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/pooled/dev'\n\nThe 'lotte/pooled/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=2,428,854\n\n\nThis dataset is used by: 'lotte_pooled_dev_forum', 'lotte_pooled_dev_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
127dfc62ed16c3b1333ab5da0acc1b8b549953db |
# Dataset Card for `lotte/pooled/dev/forum`
The `lotte/pooled/dev/forum` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/pooled/dev/forum).
# Data
This dataset provides:
- `queries` (i.e., topics); count=10,097
- `qrels`: (relevance assessments); count=68,685
- For `docs`, use [`irds/lotte_pooled_dev`](https://huggingface.co/datasets/irds/lotte_pooled_dev)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_pooled_dev_forum', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_pooled_dev_forum', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_pooled_dev_forum | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_pooled_dev",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:11:13+00:00 | {"source_datasets": ["irds/lotte_pooled_dev"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/pooled/dev/forum`", "viewer": false} | 2023-01-05T03:11:19+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_pooled_dev #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/pooled/dev/forum'
The 'lotte/pooled/dev/forum' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=10,097
- 'qrels': (relevance assessments); count=68,685
- For 'docs', use 'irds/lotte_pooled_dev'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/pooled/dev/forum'\n\nThe 'lotte/pooled/dev/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10,097\n - 'qrels': (relevance assessments); count=68,685\n\n - For 'docs', use 'irds/lotte_pooled_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_pooled_dev #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/pooled/dev/forum'\n\nThe 'lotte/pooled/dev/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10,097\n - 'qrels': (relevance assessments); count=68,685\n\n - For 'docs', use 'irds/lotte_pooled_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
cfbe6f21d7ddfb6d2ecae29a28492f01bf9be7e6 |
# Dataset Card for `lotte/pooled/dev/search`
The `lotte/pooled/dev/search` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/pooled/dev/search).
# Data
This dataset provides:
- `queries` (i.e., topics); count=2,931
- `qrels`: (relevance assessments); count=8,573
- For `docs`, use [`irds/lotte_pooled_dev`](https://huggingface.co/datasets/irds/lotte_pooled_dev)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_pooled_dev_search', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_pooled_dev_search', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_pooled_dev_search | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_pooled_dev",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:11:24+00:00 | {"source_datasets": ["irds/lotte_pooled_dev"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/pooled/dev/search`", "viewer": false} | 2023-01-05T03:11:30+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_pooled_dev #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/pooled/dev/search'
The 'lotte/pooled/dev/search' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=2,931
- 'qrels': (relevance assessments); count=8,573
- For 'docs', use 'irds/lotte_pooled_dev'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/pooled/dev/search'\n\nThe 'lotte/pooled/dev/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,931\n - 'qrels': (relevance assessments); count=8,573\n\n - For 'docs', use 'irds/lotte_pooled_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_pooled_dev #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/pooled/dev/search'\n\nThe 'lotte/pooled/dev/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,931\n - 'qrels': (relevance assessments); count=8,573\n\n - For 'docs', use 'irds/lotte_pooled_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
91603bc7ba09a81c628f3b2d9f1a782143f40ce3 |
# Dataset Card for `lotte/pooled/test`
The `lotte/pooled/test` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/pooled/test).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=2,819,103
This dataset is used by: [`lotte_pooled_test_forum`](https://huggingface.co/datasets/irds/lotte_pooled_test_forum), [`lotte_pooled_test_search`](https://huggingface.co/datasets/irds/lotte_pooled_test_search)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/lotte_pooled_test', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_pooled_test | [
"task_categories:text-retrieval",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:11:35+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/pooled/test`", "viewer": false} | 2023-01-05T03:11:41+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/pooled/test'
The 'lotte/pooled/test' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=2,819,103
This dataset is used by: 'lotte_pooled_test_forum', 'lotte_pooled_test_search'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/pooled/test'\n\nThe 'lotte/pooled/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=2,819,103\n\n\nThis dataset is used by: 'lotte_pooled_test_forum', 'lotte_pooled_test_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/pooled/test'\n\nThe 'lotte/pooled/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=2,819,103\n\n\nThis dataset is used by: 'lotte_pooled_test_forum', 'lotte_pooled_test_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
a0912b9914a6c53212691633b21328283b6cebfc |
# Dataset Card for `lotte/pooled/test/forum`
The `lotte/pooled/test/forum` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/pooled/test/forum).
# Data
This dataset provides:
- `queries` (i.e., topics); count=10,025
- `qrels`: (relevance assessments); count=61,536
- For `docs`, use [`irds/lotte_pooled_test`](https://huggingface.co/datasets/irds/lotte_pooled_test)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_pooled_test_forum', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_pooled_test_forum', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_pooled_test_forum | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_pooled_test",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:11:47+00:00 | {"source_datasets": ["irds/lotte_pooled_test"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/pooled/test/forum`", "viewer": false} | 2023-01-05T03:11:52+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_pooled_test #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/pooled/test/forum'
The 'lotte/pooled/test/forum' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=10,025
- 'qrels': (relevance assessments); count=61,536
- For 'docs', use 'irds/lotte_pooled_test'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/pooled/test/forum'\n\nThe 'lotte/pooled/test/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10,025\n - 'qrels': (relevance assessments); count=61,536\n\n - For 'docs', use 'irds/lotte_pooled_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_pooled_test #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/pooled/test/forum'\n\nThe 'lotte/pooled/test/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10,025\n - 'qrels': (relevance assessments); count=61,536\n\n - For 'docs', use 'irds/lotte_pooled_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
5ee27e33ba7515cfdd0845c2792186d4f1ef1e65 |
# Dataset Card for `lotte/pooled/test/search`
The `lotte/pooled/test/search` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/pooled/test/search).
# Data
This dataset provides:
- `queries` (i.e., topics); count=3,869
- `qrels`: (relevance assessments); count=11,124
- For `docs`, use [`irds/lotte_pooled_test`](https://huggingface.co/datasets/irds/lotte_pooled_test)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_pooled_test_search', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_pooled_test_search', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_pooled_test_search | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_pooled_test",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:11:58+00:00 | {"source_datasets": ["irds/lotte_pooled_test"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/pooled/test/search`", "viewer": false} | 2023-01-05T03:12:03+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_pooled_test #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/pooled/test/search'
The 'lotte/pooled/test/search' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=3,869
- 'qrels': (relevance assessments); count=11,124
- For 'docs', use 'irds/lotte_pooled_test'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/pooled/test/search'\n\nThe 'lotte/pooled/test/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=3,869\n - 'qrels': (relevance assessments); count=11,124\n\n - For 'docs', use 'irds/lotte_pooled_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_pooled_test #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/pooled/test/search'\n\nThe 'lotte/pooled/test/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=3,869\n - 'qrels': (relevance assessments); count=11,124\n\n - For 'docs', use 'irds/lotte_pooled_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
192ef68528f6dc82a600c33417e35201770b174d |
# Dataset Card for `lotte/recreation/dev`
The `lotte/recreation/dev` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/recreation/dev).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=263,025
This dataset is used by: [`lotte_recreation_dev_forum`](https://huggingface.co/datasets/irds/lotte_recreation_dev_forum), [`lotte_recreation_dev_search`](https://huggingface.co/datasets/irds/lotte_recreation_dev_search)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/lotte_recreation_dev', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_recreation_dev | [
"task_categories:text-retrieval",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:12:09+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/recreation/dev`", "viewer": false} | 2023-01-05T03:12:15+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/recreation/dev'
The 'lotte/recreation/dev' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=263,025
This dataset is used by: 'lotte_recreation_dev_forum', 'lotte_recreation_dev_search'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/recreation/dev'\n\nThe 'lotte/recreation/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=263,025\n\n\nThis dataset is used by: 'lotte_recreation_dev_forum', 'lotte_recreation_dev_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/recreation/dev'\n\nThe 'lotte/recreation/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=263,025\n\n\nThis dataset is used by: 'lotte_recreation_dev_forum', 'lotte_recreation_dev_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
7079c9382a7a969d3aeb1f0bdb30343b3a76c9ce |
# Dataset Card for `lotte/recreation/dev/forum`
The `lotte/recreation/dev/forum` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/recreation/dev/forum).
# Data
This dataset provides:
- `queries` (i.e., topics); count=2,002
- `qrels`: (relevance assessments); count=12,752
- For `docs`, use [`irds/lotte_recreation_dev`](https://huggingface.co/datasets/irds/lotte_recreation_dev)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_recreation_dev_forum', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_recreation_dev_forum', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_recreation_dev_forum | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_recreation_dev",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:12:20+00:00 | {"source_datasets": ["irds/lotte_recreation_dev"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/recreation/dev/forum`", "viewer": false} | 2023-01-05T03:12:26+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_recreation_dev #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/recreation/dev/forum'
The 'lotte/recreation/dev/forum' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=2,002
- 'qrels': (relevance assessments); count=12,752
- For 'docs', use 'irds/lotte_recreation_dev'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/recreation/dev/forum'\n\nThe 'lotte/recreation/dev/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,002\n - 'qrels': (relevance assessments); count=12,752\n\n - For 'docs', use 'irds/lotte_recreation_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_recreation_dev #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/recreation/dev/forum'\n\nThe 'lotte/recreation/dev/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,002\n - 'qrels': (relevance assessments); count=12,752\n\n - For 'docs', use 'irds/lotte_recreation_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
5fb2538e25d71328028783ff9fa647ef69a9a06c |
# Dataset Card for `lotte/recreation/dev/search`
The `lotte/recreation/dev/search` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/recreation/dev/search).
# Data
This dataset provides:
- `queries` (i.e., topics); count=563
- `qrels`: (relevance assessments); count=1,754
- For `docs`, use [`irds/lotte_recreation_dev`](https://huggingface.co/datasets/irds/lotte_recreation_dev)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_recreation_dev_search', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_recreation_dev_search', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_recreation_dev_search | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_recreation_dev",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:12:31+00:00 | {"source_datasets": ["irds/lotte_recreation_dev"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/recreation/dev/search`", "viewer": false} | 2023-01-05T03:12:37+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_recreation_dev #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/recreation/dev/search'
The 'lotte/recreation/dev/search' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=563
- 'qrels': (relevance assessments); count=1,754
- For 'docs', use 'irds/lotte_recreation_dev'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/recreation/dev/search'\n\nThe 'lotte/recreation/dev/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=563\n - 'qrels': (relevance assessments); count=1,754\n\n - For 'docs', use 'irds/lotte_recreation_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_recreation_dev #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/recreation/dev/search'\n\nThe 'lotte/recreation/dev/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=563\n - 'qrels': (relevance assessments); count=1,754\n\n - For 'docs', use 'irds/lotte_recreation_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
9bc24e76ed6b96b5cee6f99e09caccfa7dca1915 |
# Dataset Card for `lotte/recreation/test`
The `lotte/recreation/test` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/recreation/test).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=166,975
This dataset is used by: [`lotte_recreation_test_forum`](https://huggingface.co/datasets/irds/lotte_recreation_test_forum), [`lotte_recreation_test_search`](https://huggingface.co/datasets/irds/lotte_recreation_test_search)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/lotte_recreation_test', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_recreation_test | [
"task_categories:text-retrieval",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:12:42+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/recreation/test`", "viewer": false} | 2023-01-05T03:12:48+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/recreation/test'
The 'lotte/recreation/test' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=166,975
This dataset is used by: 'lotte_recreation_test_forum', 'lotte_recreation_test_search'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/recreation/test'\n\nThe 'lotte/recreation/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=166,975\n\n\nThis dataset is used by: 'lotte_recreation_test_forum', 'lotte_recreation_test_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/recreation/test'\n\nThe 'lotte/recreation/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=166,975\n\n\nThis dataset is used by: 'lotte_recreation_test_forum', 'lotte_recreation_test_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
6176527b4e32c49bb0b84e6940bd621753bf2000 |
# Dataset Card for `lotte/recreation/test/forum`
The `lotte/recreation/test/forum` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/recreation/test/forum).
# Data
This dataset provides:
- `queries` (i.e., topics); count=2,002
- `qrels`: (relevance assessments); count=6,947
- For `docs`, use [`irds/lotte_recreation_test`](https://huggingface.co/datasets/irds/lotte_recreation_test)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_recreation_test_forum', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_recreation_test_forum', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_recreation_test_forum | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_recreation_test",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:12:53+00:00 | {"source_datasets": ["irds/lotte_recreation_test"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/recreation/test/forum`", "viewer": false} | 2023-01-05T03:12:59+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_recreation_test #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/recreation/test/forum'
The 'lotte/recreation/test/forum' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=2,002
- 'qrels': (relevance assessments); count=6,947
- For 'docs', use 'irds/lotte_recreation_test'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/recreation/test/forum'\n\nThe 'lotte/recreation/test/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,002\n - 'qrels': (relevance assessments); count=6,947\n\n - For 'docs', use 'irds/lotte_recreation_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_recreation_test #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/recreation/test/forum'\n\nThe 'lotte/recreation/test/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,002\n - 'qrels': (relevance assessments); count=6,947\n\n - For 'docs', use 'irds/lotte_recreation_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
e7ac4a98a196497f7c525868d34dc0dbd568802b |
# Dataset Card for `lotte/recreation/test/search`
The `lotte/recreation/test/search` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/recreation/test/search).
# Data
This dataset provides:
- `queries` (i.e., topics); count=924
- `qrels`: (relevance assessments); count=1,991
- For `docs`, use [`irds/lotte_recreation_test`](https://huggingface.co/datasets/irds/lotte_recreation_test)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_recreation_test_search', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_recreation_test_search', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_recreation_test_search | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_recreation_test",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:13:04+00:00 | {"source_datasets": ["irds/lotte_recreation_test"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/recreation/test/search`", "viewer": false} | 2023-01-05T03:13:10+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_recreation_test #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/recreation/test/search'
The 'lotte/recreation/test/search' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=924
- 'qrels': (relevance assessments); count=1,991
- For 'docs', use 'irds/lotte_recreation_test'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/recreation/test/search'\n\nThe 'lotte/recreation/test/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=924\n - 'qrels': (relevance assessments); count=1,991\n\n - For 'docs', use 'irds/lotte_recreation_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_recreation_test #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/recreation/test/search'\n\nThe 'lotte/recreation/test/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=924\n - 'qrels': (relevance assessments); count=1,991\n\n - For 'docs', use 'irds/lotte_recreation_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
7e9d0fba97c5553fe1e84f07b681383b7078b662 |
# Dataset Card for `lotte/science/dev`
The `lotte/science/dev` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/science/dev).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=343,642
This dataset is used by: [`lotte_science_dev_forum`](https://huggingface.co/datasets/irds/lotte_science_dev_forum), [`lotte_science_dev_search`](https://huggingface.co/datasets/irds/lotte_science_dev_search)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/lotte_science_dev', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_science_dev | [
"task_categories:text-retrieval",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:13:16+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/science/dev`", "viewer": false} | 2023-01-05T03:13:21+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/science/dev'
The 'lotte/science/dev' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=343,642
This dataset is used by: 'lotte_science_dev_forum', 'lotte_science_dev_search'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/science/dev'\n\nThe 'lotte/science/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=343,642\n\n\nThis dataset is used by: 'lotte_science_dev_forum', 'lotte_science_dev_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/science/dev'\n\nThe 'lotte/science/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=343,642\n\n\nThis dataset is used by: 'lotte_science_dev_forum', 'lotte_science_dev_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
feb4f854a3b8fb64c0dd0ded0653b30c2e92d9df |
# Dataset Card for `lotte/science/dev/forum`
The `lotte/science/dev/forum` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/science/dev/forum).
# Data
This dataset provides:
- `queries` (i.e., topics); count=2,013
- `qrels`: (relevance assessments); count=12,271
- For `docs`, use [`irds/lotte_science_dev`](https://huggingface.co/datasets/irds/lotte_science_dev)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_science_dev_forum', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_science_dev_forum', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_science_dev_forum | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_science_dev",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:13:27+00:00 | {"source_datasets": ["irds/lotte_science_dev"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/science/dev/forum`", "viewer": false} | 2023-01-05T03:13:32+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_science_dev #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/science/dev/forum'
The 'lotte/science/dev/forum' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=2,013
- 'qrels': (relevance assessments); count=12,271
- For 'docs', use 'irds/lotte_science_dev'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/science/dev/forum'\n\nThe 'lotte/science/dev/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,013\n - 'qrels': (relevance assessments); count=12,271\n\n - For 'docs', use 'irds/lotte_science_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_science_dev #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/science/dev/forum'\n\nThe 'lotte/science/dev/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,013\n - 'qrels': (relevance assessments); count=12,271\n\n - For 'docs', use 'irds/lotte_science_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
53364075c982cbc9b3f3ad72eb7047977c8f3323 |
# Dataset Card for `lotte/science/dev/search`
The `lotte/science/dev/search` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/science/dev/search).
# Data
This dataset provides:
- `queries` (i.e., topics); count=538
- `qrels`: (relevance assessments); count=1,480
- For `docs`, use [`irds/lotte_science_dev`](https://huggingface.co/datasets/irds/lotte_science_dev)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_science_dev_search', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_science_dev_search', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_science_dev_search | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_science_dev",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:13:38+00:00 | {"source_datasets": ["irds/lotte_science_dev"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/science/dev/search`", "viewer": false} | 2023-01-05T03:13:44+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_science_dev #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/science/dev/search'
The 'lotte/science/dev/search' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=538
- 'qrels': (relevance assessments); count=1,480
- For 'docs', use 'irds/lotte_science_dev'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/science/dev/search'\n\nThe 'lotte/science/dev/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=538\n - 'qrels': (relevance assessments); count=1,480\n\n - For 'docs', use 'irds/lotte_science_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_science_dev #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/science/dev/search'\n\nThe 'lotte/science/dev/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=538\n - 'qrels': (relevance assessments); count=1,480\n\n - For 'docs', use 'irds/lotte_science_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
4059e65b15287127004aa66b766fc71f5409dd12 |
# Dataset Card for `lotte/science/test`
The `lotte/science/test` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/science/test).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=1,694,164
This dataset is used by: [`lotte_science_test_forum`](https://huggingface.co/datasets/irds/lotte_science_test_forum), [`lotte_science_test_search`](https://huggingface.co/datasets/irds/lotte_science_test_search)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/lotte_science_test', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_science_test | [
"task_categories:text-retrieval",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:13:49+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/science/test`", "viewer": false} | 2023-01-05T03:13:55+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/science/test'
The 'lotte/science/test' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=1,694,164
This dataset is used by: 'lotte_science_test_forum', 'lotte_science_test_search'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/science/test'\n\nThe 'lotte/science/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=1,694,164\n\n\nThis dataset is used by: 'lotte_science_test_forum', 'lotte_science_test_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/science/test'\n\nThe 'lotte/science/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=1,694,164\n\n\nThis dataset is used by: 'lotte_science_test_forum', 'lotte_science_test_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
72766e322efb20dfea29cc70907c5d1b517b8508 |
# Dataset Card for `lotte/science/test/forum`
The `lotte/science/test/forum` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/science/test/forum).
# Data
This dataset provides:
- `queries` (i.e., topics); count=2,017
- `qrels`: (relevance assessments); count=15,515
- For `docs`, use [`irds/lotte_science_test`](https://huggingface.co/datasets/irds/lotte_science_test)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_science_test_forum', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_science_test_forum', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_science_test_forum | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_science_test",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:14:00+00:00 | {"source_datasets": ["irds/lotte_science_test"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/science/test/forum`", "viewer": false} | 2023-01-05T03:14:06+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_science_test #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/science/test/forum'
The 'lotte/science/test/forum' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=2,017
- 'qrels': (relevance assessments); count=15,515
- For 'docs', use 'irds/lotte_science_test'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/science/test/forum'\n\nThe 'lotte/science/test/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,017\n - 'qrels': (relevance assessments); count=15,515\n\n - For 'docs', use 'irds/lotte_science_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_science_test #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/science/test/forum'\n\nThe 'lotte/science/test/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,017\n - 'qrels': (relevance assessments); count=15,515\n\n - For 'docs', use 'irds/lotte_science_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
d48e8ba8cd88b2e05ef4e8c641d6048913630f13 |
# Dataset Card for `lotte/science/test/search`
The `lotte/science/test/search` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/science/test/search).
# Data
This dataset provides:
- `queries` (i.e., topics); count=617
- `qrels`: (relevance assessments); count=1,738
- For `docs`, use [`irds/lotte_science_test`](https://huggingface.co/datasets/irds/lotte_science_test)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_science_test_search', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_science_test_search', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_science_test_search | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_science_test",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:14:11+00:00 | {"source_datasets": ["irds/lotte_science_test"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/science/test/search`", "viewer": false} | 2023-01-05T03:14:17+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_science_test #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/science/test/search'
The 'lotte/science/test/search' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=617
- 'qrels': (relevance assessments); count=1,738
- For 'docs', use 'irds/lotte_science_test'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/science/test/search'\n\nThe 'lotte/science/test/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=617\n - 'qrels': (relevance assessments); count=1,738\n\n - For 'docs', use 'irds/lotte_science_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_science_test #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/science/test/search'\n\nThe 'lotte/science/test/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=617\n - 'qrels': (relevance assessments); count=1,738\n\n - For 'docs', use 'irds/lotte_science_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
5633be42bae0d79cd1e695c9adba7c7db7765675 |
# Dataset Card for `lotte/technology/dev`
The `lotte/technology/dev` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/technology/dev).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=1,276,222
This dataset is used by: [`lotte_technology_dev_forum`](https://huggingface.co/datasets/irds/lotte_technology_dev_forum), [`lotte_technology_dev_search`](https://huggingface.co/datasets/irds/lotte_technology_dev_search)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/lotte_technology_dev', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_technology_dev | [
"task_categories:text-retrieval",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:14:22+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/technology/dev`", "viewer": false} | 2023-01-05T03:14:28+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/technology/dev'
The 'lotte/technology/dev' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=1,276,222
This dataset is used by: 'lotte_technology_dev_forum', 'lotte_technology_dev_search'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/technology/dev'\n\nThe 'lotte/technology/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=1,276,222\n\n\nThis dataset is used by: 'lotte_technology_dev_forum', 'lotte_technology_dev_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/technology/dev'\n\nThe 'lotte/technology/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=1,276,222\n\n\nThis dataset is used by: 'lotte_technology_dev_forum', 'lotte_technology_dev_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
a88b3bbcce8322c4164cafccb9e1f4e45c70b90f |
# Dataset Card for `lotte/technology/dev/forum`
The `lotte/technology/dev/forum` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/technology/dev/forum).
# Data
This dataset provides:
- `queries` (i.e., topics); count=2,003
- `qrels`: (relevance assessments); count=15,741
- For `docs`, use [`irds/lotte_technology_dev`](https://huggingface.co/datasets/irds/lotte_technology_dev)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_technology_dev_forum', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_technology_dev_forum', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_technology_dev_forum | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_technology_dev",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:14:34+00:00 | {"source_datasets": ["irds/lotte_technology_dev"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/technology/dev/forum`", "viewer": false} | 2023-01-05T03:14:40+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_technology_dev #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/technology/dev/forum'
The 'lotte/technology/dev/forum' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=2,003
- 'qrels': (relevance assessments); count=15,741
- For 'docs', use 'irds/lotte_technology_dev'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/technology/dev/forum'\n\nThe 'lotte/technology/dev/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,003\n - 'qrels': (relevance assessments); count=15,741\n\n - For 'docs', use 'irds/lotte_technology_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_technology_dev #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/technology/dev/forum'\n\nThe 'lotte/technology/dev/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,003\n - 'qrels': (relevance assessments); count=15,741\n\n - For 'docs', use 'irds/lotte_technology_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
daae9c829591e515e2f214b6116f595c2bb99011 |
# Dataset Card for `lotte/technology/dev/search`
The `lotte/technology/dev/search` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/technology/dev/search).
# Data
This dataset provides:
- `queries` (i.e., topics); count=916
- `qrels`: (relevance assessments); count=2,676
- For `docs`, use [`irds/lotte_technology_dev`](https://huggingface.co/datasets/irds/lotte_technology_dev)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_technology_dev_search', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_technology_dev_search', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_technology_dev_search | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_technology_dev",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:14:45+00:00 | {"source_datasets": ["irds/lotte_technology_dev"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/technology/dev/search`", "viewer": false} | 2023-01-05T03:14:51+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_technology_dev #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/technology/dev/search'
The 'lotte/technology/dev/search' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=916
- 'qrels': (relevance assessments); count=2,676
- For 'docs', use 'irds/lotte_technology_dev'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/technology/dev/search'\n\nThe 'lotte/technology/dev/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=916\n - 'qrels': (relevance assessments); count=2,676\n\n - For 'docs', use 'irds/lotte_technology_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_technology_dev #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/technology/dev/search'\n\nThe 'lotte/technology/dev/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=916\n - 'qrels': (relevance assessments); count=2,676\n\n - For 'docs', use 'irds/lotte_technology_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
bca4f7c1356530ab45196bfe991c138142961db5 |
# Dataset Card for `lotte/technology/test`
The `lotte/technology/test` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/technology/test).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=638,509
This dataset is used by: [`lotte_technology_test_forum`](https://huggingface.co/datasets/irds/lotte_technology_test_forum), [`lotte_technology_test_search`](https://huggingface.co/datasets/irds/lotte_technology_test_search)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/lotte_technology_test', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_technology_test | [
"task_categories:text-retrieval",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:14:56+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/technology/test`", "viewer": false} | 2023-01-05T03:15:02+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/technology/test'
The 'lotte/technology/test' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=638,509
This dataset is used by: 'lotte_technology_test_forum', 'lotte_technology_test_search'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/technology/test'\n\nThe 'lotte/technology/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=638,509\n\n\nThis dataset is used by: 'lotte_technology_test_forum', 'lotte_technology_test_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/technology/test'\n\nThe 'lotte/technology/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=638,509\n\n\nThis dataset is used by: 'lotte_technology_test_forum', 'lotte_technology_test_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
35ad62166a3d2daf366df949a86a3ab511c34deb |
# Dataset Card for `lotte/technology/test/forum`
The `lotte/technology/test/forum` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/technology/test/forum).
# Data
This dataset provides:
- `queries` (i.e., topics); count=2,004
- `qrels`: (relevance assessments); count=15,890
- For `docs`, use [`irds/lotte_technology_test`](https://huggingface.co/datasets/irds/lotte_technology_test)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_technology_test_forum', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_technology_test_forum', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_technology_test_forum | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_technology_test",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:15:07+00:00 | {"source_datasets": ["irds/lotte_technology_test"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/technology/test/forum`", "viewer": false} | 2023-01-05T03:15:13+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_technology_test #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/technology/test/forum'
The 'lotte/technology/test/forum' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=2,004
- 'qrels': (relevance assessments); count=15,890
- For 'docs', use 'irds/lotte_technology_test'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/technology/test/forum'\n\nThe 'lotte/technology/test/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,004\n - 'qrels': (relevance assessments); count=15,890\n\n - For 'docs', use 'irds/lotte_technology_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_technology_test #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/technology/test/forum'\n\nThe 'lotte/technology/test/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,004\n - 'qrels': (relevance assessments); count=15,890\n\n - For 'docs', use 'irds/lotte_technology_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
20dcea7394f3b955ada24c19e6cbe332592e9cc8 |
# Dataset Card for `lotte/technology/test/search`
The `lotte/technology/test/search` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/technology/test/search).
# Data
This dataset provides:
- `queries` (i.e., topics); count=596
- `qrels`: (relevance assessments); count=2,045
- For `docs`, use [`irds/lotte_technology_test`](https://huggingface.co/datasets/irds/lotte_technology_test)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_technology_test_search', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_technology_test_search', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_technology_test_search | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_technology_test",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:15:18+00:00 | {"source_datasets": ["irds/lotte_technology_test"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/technology/test/search`", "viewer": false} | 2023-01-05T03:15:24+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_technology_test #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/technology/test/search'
The 'lotte/technology/test/search' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=596
- 'qrels': (relevance assessments); count=2,045
- For 'docs', use 'irds/lotte_technology_test'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/technology/test/search'\n\nThe 'lotte/technology/test/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=596\n - 'qrels': (relevance assessments); count=2,045\n\n - For 'docs', use 'irds/lotte_technology_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_technology_test #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/technology/test/search'\n\nThe 'lotte/technology/test/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=596\n - 'qrels': (relevance assessments); count=2,045\n\n - For 'docs', use 'irds/lotte_technology_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
246bfbafd2636eb22716863a659ea11f6ca95319 |
# Dataset Card for `lotte/writing/dev`
The `lotte/writing/dev` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/writing/dev).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=277,072
This dataset is used by: [`lotte_writing_dev_forum`](https://huggingface.co/datasets/irds/lotte_writing_dev_forum), [`lotte_writing_dev_search`](https://huggingface.co/datasets/irds/lotte_writing_dev_search)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/lotte_writing_dev', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_writing_dev | [
"task_categories:text-retrieval",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:15:29+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/writing/dev`", "viewer": false} | 2023-01-05T03:15:35+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/writing/dev'
The 'lotte/writing/dev' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=277,072
This dataset is used by: 'lotte_writing_dev_forum', 'lotte_writing_dev_search'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/writing/dev'\n\nThe 'lotte/writing/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=277,072\n\n\nThis dataset is used by: 'lotte_writing_dev_forum', 'lotte_writing_dev_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/writing/dev'\n\nThe 'lotte/writing/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=277,072\n\n\nThis dataset is used by: 'lotte_writing_dev_forum', 'lotte_writing_dev_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
4a76341cc5d41f67ec0870886a6dac234bb22f91 |
# Dataset Card for `lotte/writing/dev/forum`
The `lotte/writing/dev/forum` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/writing/dev/forum).
# Data
This dataset provides:
- `queries` (i.e., topics); count=2,003
- `qrels`: (relevance assessments); count=15,098
- For `docs`, use [`irds/lotte_writing_dev`](https://huggingface.co/datasets/irds/lotte_writing_dev)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_writing_dev_forum', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_writing_dev_forum', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_writing_dev_forum | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_writing_dev",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:15:41+00:00 | {"source_datasets": ["irds/lotte_writing_dev"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/writing/dev/forum`", "viewer": false} | 2023-01-05T03:15:46+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_writing_dev #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/writing/dev/forum'
The 'lotte/writing/dev/forum' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=2,003
- 'qrels': (relevance assessments); count=15,098
- For 'docs', use 'irds/lotte_writing_dev'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/writing/dev/forum'\n\nThe 'lotte/writing/dev/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,003\n - 'qrels': (relevance assessments); count=15,098\n\n - For 'docs', use 'irds/lotte_writing_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_writing_dev #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/writing/dev/forum'\n\nThe 'lotte/writing/dev/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,003\n - 'qrels': (relevance assessments); count=15,098\n\n - For 'docs', use 'irds/lotte_writing_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
9d041d8753acfd4c26ae53cb609a544ce0ef76ad |
# Dataset Card for `lotte/writing/dev/search`
The `lotte/writing/dev/search` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/writing/dev/search).
# Data
This dataset provides:
- `queries` (i.e., topics); count=497
- `qrels`: (relevance assessments); count=1,287
- For `docs`, use [`irds/lotte_writing_dev`](https://huggingface.co/datasets/irds/lotte_writing_dev)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_writing_dev_search', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_writing_dev_search', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_writing_dev_search | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_writing_dev",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:15:52+00:00 | {"source_datasets": ["irds/lotte_writing_dev"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/writing/dev/search`", "viewer": false} | 2023-01-05T03:15:57+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_writing_dev #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/writing/dev/search'
The 'lotte/writing/dev/search' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=497
- 'qrels': (relevance assessments); count=1,287
- For 'docs', use 'irds/lotte_writing_dev'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/writing/dev/search'\n\nThe 'lotte/writing/dev/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=497\n - 'qrels': (relevance assessments); count=1,287\n\n - For 'docs', use 'irds/lotte_writing_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_writing_dev #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/writing/dev/search'\n\nThe 'lotte/writing/dev/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=497\n - 'qrels': (relevance assessments); count=1,287\n\n - For 'docs', use 'irds/lotte_writing_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
de44627f761d60dd2769ad90e2c98ea8a9fcd028 |
# Dataset Card for `lotte/writing/test`
The `lotte/writing/test` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/writing/test).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=199,994
This dataset is used by: [`lotte_writing_test_forum`](https://huggingface.co/datasets/irds/lotte_writing_test_forum), [`lotte_writing_test_search`](https://huggingface.co/datasets/irds/lotte_writing_test_search)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/lotte_writing_test', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_writing_test | [
"task_categories:text-retrieval",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:16:03+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/writing/test`", "viewer": false} | 2023-01-05T03:16:09+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/writing/test'
The 'lotte/writing/test' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=199,994
This dataset is used by: 'lotte_writing_test_forum', 'lotte_writing_test_search'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/writing/test'\n\nThe 'lotte/writing/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=199,994\n\n\nThis dataset is used by: 'lotte_writing_test_forum', 'lotte_writing_test_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/writing/test'\n\nThe 'lotte/writing/test' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=199,994\n\n\nThis dataset is used by: 'lotte_writing_test_forum', 'lotte_writing_test_search'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
85c7c48d74c90c327785119dfcaf941809841631 |
# Dataset Card for `lotte/writing/test/forum`
The `lotte/writing/test/forum` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/writing/test/forum).
# Data
This dataset provides:
- `queries` (i.e., topics); count=2,000
- `qrels`: (relevance assessments); count=12,906
- For `docs`, use [`irds/lotte_writing_test`](https://huggingface.co/datasets/irds/lotte_writing_test)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_writing_test_forum', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_writing_test_forum', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_writing_test_forum | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_writing_test",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:16:14+00:00 | {"source_datasets": ["irds/lotte_writing_test"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/writing/test/forum`", "viewer": false} | 2023-01-05T03:16:21+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_writing_test #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/writing/test/forum'
The 'lotte/writing/test/forum' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=2,000
- 'qrels': (relevance assessments); count=12,906
- For 'docs', use 'irds/lotte_writing_test'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/writing/test/forum'\n\nThe 'lotte/writing/test/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,000\n - 'qrels': (relevance assessments); count=12,906\n\n - For 'docs', use 'irds/lotte_writing_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_writing_test #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/writing/test/forum'\n\nThe 'lotte/writing/test/forum' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=2,000\n - 'qrels': (relevance assessments); count=12,906\n\n - For 'docs', use 'irds/lotte_writing_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
8fdc4cc96dc63ab67aa866752b207e5f7038d15d |
# Dataset Card for `lotte/writing/test/search`
The `lotte/writing/test/search` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/writing/test/search).
# Data
This dataset provides:
- `queries` (i.e., topics); count=1,071
- `qrels`: (relevance assessments); count=3,546
- For `docs`, use [`irds/lotte_writing_test`](https://huggingface.co/datasets/irds/lotte_writing_test)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_writing_test_search', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_writing_test_search', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
| irds/lotte_writing_test_search | [
"task_categories:text-retrieval",
"source_datasets:irds/lotte_writing_test",
"arxiv:2112.01488",
"region:us"
] | 2023-01-05T03:16:27+00:00 | {"source_datasets": ["irds/lotte_writing_test"], "task_categories": ["text-retrieval"], "pretty_name": "`lotte/writing/test/search`", "viewer": false} | 2023-01-05T03:16:33+00:00 | [
"2112.01488"
] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/lotte_writing_test #arxiv-2112.01488 #region-us
|
# Dataset Card for 'lotte/writing/test/search'
The 'lotte/writing/test/search' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=1,071
- 'qrels': (relevance assessments); count=3,546
- For 'docs', use 'irds/lotte_writing_test'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'lotte/writing/test/search'\n\nThe 'lotte/writing/test/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=1,071\n - 'qrels': (relevance assessments); count=3,546\n\n - For 'docs', use 'irds/lotte_writing_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/lotte_writing_test #arxiv-2112.01488 #region-us \n",
"# Dataset Card for 'lotte/writing/test/search'\n\nThe 'lotte/writing/test/search' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=1,071\n - 'qrels': (relevance assessments); count=3,546\n\n - For 'docs', use 'irds/lotte_writing_test'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
8945d071d1c2e1a986e9c4c8e23d413d1607456b |
# Dataset Card for `msmarco-passage`
The `msmarco-passage` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/msmarco-passage#msmarco-passage).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=8,841,823
This dataset is used by: [`msmarco-passage_dev`](https://huggingface.co/datasets/irds/msmarco-passage_dev), [`msmarco-passage_dev_judged`](https://huggingface.co/datasets/irds/msmarco-passage_dev_judged), [`msmarco-passage_eval`](https://huggingface.co/datasets/irds/msmarco-passage_eval), [`msmarco-passage_train_triples-small`](https://huggingface.co/datasets/irds/msmarco-passage_train_triples-small), [`msmarco-passage_train_triples-v2`](https://huggingface.co/datasets/irds/msmarco-passage_train_triples-v2), [`msmarco-passage_trec-dl-hard`](https://huggingface.co/datasets/irds/msmarco-passage_trec-dl-hard), [`msmarco-passage_trec-dl-hard_fold1`](https://huggingface.co/datasets/irds/msmarco-passage_trec-dl-hard_fold1), [`msmarco-passage_trec-dl-hard_fold2`](https://huggingface.co/datasets/irds/msmarco-passage_trec-dl-hard_fold2), [`msmarco-passage_trec-dl-hard_fold3`](https://huggingface.co/datasets/irds/msmarco-passage_trec-dl-hard_fold3), [`msmarco-passage_trec-dl-hard_fold4`](https://huggingface.co/datasets/irds/msmarco-passage_trec-dl-hard_fold4), [`msmarco-passage_trec-dl-hard_fold5`](https://huggingface.co/datasets/irds/msmarco-passage_trec-dl-hard_fold5)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/msmarco-passage', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Bajaj2016Msmarco,
title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
author={Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, Tong Wang},
booktitle={InCoCo@NIPS},
year={2016}
}
```
| irds/msmarco-passage | [
"task_categories:text-retrieval",
"region:us"
] | 2023-01-05T03:16:38+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`msmarco-passage`", "viewer": false} | 2023-01-05T03:16:44+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #region-us
|
# Dataset Card for 'msmarco-passage'
The 'msmarco-passage' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=8,841,823
This dataset is used by: 'msmarco-passage_dev', 'msmarco-passage_dev_judged', 'msmarco-passage_eval', 'msmarco-passage_train_triples-small', 'msmarco-passage_train_triples-v2', 'msmarco-passage_trec-dl-hard', 'msmarco-passage_trec-dl-hard_fold1', 'msmarco-passage_trec-dl-hard_fold2', 'msmarco-passage_trec-dl-hard_fold3', 'msmarco-passage_trec-dl-hard_fold4', 'msmarco-passage_trec-dl-hard_fold5'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'msmarco-passage'\n\nThe 'msmarco-passage' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,841,823\n\n\nThis dataset is used by: 'msmarco-passage_dev', 'msmarco-passage_dev_judged', 'msmarco-passage_eval', 'msmarco-passage_train_triples-small', 'msmarco-passage_train_triples-v2', 'msmarco-passage_trec-dl-hard', 'msmarco-passage_trec-dl-hard_fold1', 'msmarco-passage_trec-dl-hard_fold2', 'msmarco-passage_trec-dl-hard_fold3', 'msmarco-passage_trec-dl-hard_fold4', 'msmarco-passage_trec-dl-hard_fold5'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #region-us \n",
"# Dataset Card for 'msmarco-passage'\n\nThe 'msmarco-passage' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,841,823\n\n\nThis dataset is used by: 'msmarco-passage_dev', 'msmarco-passage_dev_judged', 'msmarco-passage_eval', 'msmarco-passage_train_triples-small', 'msmarco-passage_train_triples-v2', 'msmarco-passage_trec-dl-hard', 'msmarco-passage_trec-dl-hard_fold1', 'msmarco-passage_trec-dl-hard_fold2', 'msmarco-passage_trec-dl-hard_fold3', 'msmarco-passage_trec-dl-hard_fold4', 'msmarco-passage_trec-dl-hard_fold5'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
404be20e8d8c396c2c82a101ea9a9ecbf8e2cfdb |
# Dataset Card for `msmarco-passage/dev`
The `msmarco-passage/dev` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/msmarco-passage#msmarco-passage/dev).
# Data
This dataset provides:
- `queries` (i.e., topics); count=101,093
- `qrels`: (relevance assessments); count=59,273
- For `docs`, use [`irds/msmarco-passage`](https://huggingface.co/datasets/irds/msmarco-passage)
This dataset is used by: [`msmarco-passage_dev_judged`](https://huggingface.co/datasets/irds/msmarco-passage_dev_judged)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/msmarco-passage_dev', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/msmarco-passage_dev', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Bajaj2016Msmarco,
title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
author={Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, Tong Wang},
booktitle={InCoCo@NIPS},
year={2016}
}
```
| irds/msmarco-passage_dev | [
"task_categories:text-retrieval",
"source_datasets:irds/msmarco-passage",
"region:us"
] | 2023-01-05T03:16:49+00:00 | {"source_datasets": ["irds/msmarco-passage"], "task_categories": ["text-retrieval"], "pretty_name": "`msmarco-passage/dev`", "viewer": false} | 2023-01-05T03:16:55+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us
|
# Dataset Card for 'msmarco-passage/dev'
The 'msmarco-passage/dev' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=101,093
- 'qrels': (relevance assessments); count=59,273
- For 'docs', use 'irds/msmarco-passage'
This dataset is used by: 'msmarco-passage_dev_judged'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'msmarco-passage/dev'\n\nThe 'msmarco-passage/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,093\n - 'qrels': (relevance assessments); count=59,273\n\n - For 'docs', use 'irds/msmarco-passage'\n\nThis dataset is used by: 'msmarco-passage_dev_judged'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us \n",
"# Dataset Card for 'msmarco-passage/dev'\n\nThe 'msmarco-passage/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,093\n - 'qrels': (relevance assessments); count=59,273\n\n - For 'docs', use 'irds/msmarco-passage'\n\nThis dataset is used by: 'msmarco-passage_dev_judged'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
8c074d85e7f17547f7b13a0c9e19ec7bc5b007b5 |
# Dataset Card for `msmarco-passage/dev/judged`
The `msmarco-passage/dev/judged` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/msmarco-passage#msmarco-passage/dev/judged).
# Data
This dataset provides:
- `queries` (i.e., topics); count=55,578
- For `docs`, use [`irds/msmarco-passage`](https://huggingface.co/datasets/irds/msmarco-passage)
- For `qrels`, use [`irds/msmarco-passage_dev`](https://huggingface.co/datasets/irds/msmarco-passage_dev)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/msmarco-passage_dev_judged', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Bajaj2016Msmarco,
title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
author={Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, Tong Wang},
booktitle={InCoCo@NIPS},
year={2016}
}
```
| irds/msmarco-passage_dev_judged | [
"task_categories:text-retrieval",
"source_datasets:irds/msmarco-passage",
"source_datasets:irds/msmarco-passage_dev",
"region:us"
] | 2023-01-05T03:17:01+00:00 | {"source_datasets": ["irds/msmarco-passage", "irds/msmarco-passage_dev"], "task_categories": ["text-retrieval"], "pretty_name": "`msmarco-passage/dev/judged`", "viewer": false} | 2023-01-05T03:17:08+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #source_datasets-irds/msmarco-passage_dev #region-us
|
# Dataset Card for 'msmarco-passage/dev/judged'
The 'msmarco-passage/dev/judged' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=55,578
- For 'docs', use 'irds/msmarco-passage'
- For 'qrels', use 'irds/msmarco-passage_dev'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'msmarco-passage/dev/judged'\n\nThe 'msmarco-passage/dev/judged' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=55,578\n\n - For 'docs', use 'irds/msmarco-passage'\n - For 'qrels', use 'irds/msmarco-passage_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #source_datasets-irds/msmarco-passage_dev #region-us \n",
"# Dataset Card for 'msmarco-passage/dev/judged'\n\nThe 'msmarco-passage/dev/judged' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=55,578\n\n - For 'docs', use 'irds/msmarco-passage'\n - For 'qrels', use 'irds/msmarco-passage_dev'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
d2321bf1ed1207ee9afba00880809436b43fc0cc |
# Dataset Card for `msmarco-passage/eval`
The `msmarco-passage/eval` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/msmarco-passage#msmarco-passage/eval).
# Data
This dataset provides:
- `queries` (i.e., topics); count=101,092
- For `docs`, use [`irds/msmarco-passage`](https://huggingface.co/datasets/irds/msmarco-passage)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/msmarco-passage_eval', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Bajaj2016Msmarco,
title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
author={Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, Tong Wang},
booktitle={InCoCo@NIPS},
year={2016}
}
```
| irds/msmarco-passage_eval | [
"task_categories:text-retrieval",
"source_datasets:irds/msmarco-passage",
"region:us"
] | 2023-01-05T03:17:13+00:00 | {"source_datasets": ["irds/msmarco-passage"], "task_categories": ["text-retrieval"], "pretty_name": "`msmarco-passage/eval`", "viewer": false} | 2023-01-05T03:17:19+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us
|
# Dataset Card for 'msmarco-passage/eval'
The 'msmarco-passage/eval' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=101,092
- For 'docs', use 'irds/msmarco-passage'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'msmarco-passage/eval'\n\nThe 'msmarco-passage/eval' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,092\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us \n",
"# Dataset Card for 'msmarco-passage/eval'\n\nThe 'msmarco-passage/eval' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,092\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
de45da64bde97a5f1f91e59ebb0f1afc64a4c988 |
# Dataset Card for `msmarco-passage/train/triples-small`
The `msmarco-passage/train/triples-small` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/msmarco-passage#msmarco-passage/train/triples-small).
# Data
This dataset provides:
- `docpairs`; count=39,780,811
- For `docs`, use [`irds/msmarco-passage`](https://huggingface.co/datasets/irds/msmarco-passage)
## Usage
```python
from datasets import load_dataset
docpairs = load_dataset('irds/msmarco-passage_train_triples-small', 'docpairs')
for record in docpairs:
record # {'query_id': ..., 'doc_id_a': ..., 'doc_id_b': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Bajaj2016Msmarco,
title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
author={Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, Tong Wang},
booktitle={InCoCo@NIPS},
year={2016}
}
```
| irds/msmarco-passage_train_triples-small | [
"task_categories:text-retrieval",
"source_datasets:irds/msmarco-passage",
"region:us"
] | 2023-01-05T03:17:25+00:00 | {"source_datasets": ["irds/msmarco-passage"], "task_categories": ["text-retrieval"], "pretty_name": "`msmarco-passage/train/triples-small`", "viewer": false} | 2023-01-05T03:17:31+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us
|
# Dataset Card for 'msmarco-passage/train/triples-small'
The 'msmarco-passage/train/triples-small' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docpairs'; count=39,780,811
- For 'docs', use 'irds/msmarco-passage'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'msmarco-passage/train/triples-small'\n\nThe 'msmarco-passage/train/triples-small' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docpairs'; count=39,780,811\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us \n",
"# Dataset Card for 'msmarco-passage/train/triples-small'\n\nThe 'msmarco-passage/train/triples-small' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docpairs'; count=39,780,811\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
7ffed33f9c1e1f94dd4d8e816ff253f4dc335ef9 |
# Dataset Card for `msmarco-passage/train/triples-v2`
The `msmarco-passage/train/triples-v2` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/msmarco-passage#msmarco-passage/train/triples-v2).
# Data
This dataset provides:
- `docpairs`; count=397,768,673
- For `docs`, use [`irds/msmarco-passage`](https://huggingface.co/datasets/irds/msmarco-passage)
## Usage
```python
from datasets import load_dataset
docpairs = load_dataset('irds/msmarco-passage_train_triples-v2', 'docpairs')
for record in docpairs:
record # {'query_id': ..., 'doc_id_a': ..., 'doc_id_b': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@inproceedings{Bajaj2016Msmarco,
title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
author={Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, Tong Wang},
booktitle={InCoCo@NIPS},
year={2016}
}
```
| irds/msmarco-passage_train_triples-v2 | [
"task_categories:text-retrieval",
"source_datasets:irds/msmarco-passage",
"region:us"
] | 2023-01-05T03:17:36+00:00 | {"source_datasets": ["irds/msmarco-passage"], "task_categories": ["text-retrieval"], "pretty_name": "`msmarco-passage/train/triples-v2`", "viewer": false} | 2023-01-05T03:17:42+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us
|
# Dataset Card for 'msmarco-passage/train/triples-v2'
The 'msmarco-passage/train/triples-v2' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docpairs'; count=397,768,673
- For 'docs', use 'irds/msmarco-passage'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'msmarco-passage/train/triples-v2'\n\nThe 'msmarco-passage/train/triples-v2' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docpairs'; count=397,768,673\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us \n",
"# Dataset Card for 'msmarco-passage/train/triples-v2'\n\nThe 'msmarco-passage/train/triples-v2' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docpairs'; count=397,768,673\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
b1129fe39c9a242ff4f864aa9b8dc6d2d23bec25 |
# Dataset Card for `msmarco-passage/trec-dl-hard`
The `msmarco-passage/trec-dl-hard` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/msmarco-passage#msmarco-passage/trec-dl-hard).
# Data
This dataset provides:
- `queries` (i.e., topics); count=50
- `qrels`: (relevance assessments); count=4,256
- For `docs`, use [`irds/msmarco-passage`](https://huggingface.co/datasets/irds/msmarco-passage)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/msmarco-passage_trec-dl-hard', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/msmarco-passage_trec-dl-hard', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Mackie2021DlHard,
title={How Deep is your Learning: the DL-HARD Annotated Deep Learning Dataset},
author={Iain Mackie and Jeffrey Dalton and Andrew Yates},
journal={ArXiv},
year={2021},
volume={abs/2105.07975}
}
@inproceedings{Bajaj2016Msmarco,
title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
author={Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, Tong Wang},
booktitle={InCoCo@NIPS},
year={2016}
}
```
| irds/msmarco-passage_trec-dl-hard | [
"task_categories:text-retrieval",
"source_datasets:irds/msmarco-passage",
"region:us"
] | 2023-01-05T03:17:47+00:00 | {"source_datasets": ["irds/msmarco-passage"], "task_categories": ["text-retrieval"], "pretty_name": "`msmarco-passage/trec-dl-hard`", "viewer": false} | 2023-01-05T03:17:54+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us
|
# Dataset Card for 'msmarco-passage/trec-dl-hard'
The 'msmarco-passage/trec-dl-hard' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=50
- 'qrels': (relevance assessments); count=4,256
- For 'docs', use 'irds/msmarco-passage'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'msmarco-passage/trec-dl-hard'\n\nThe 'msmarco-passage/trec-dl-hard' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=50\n - 'qrels': (relevance assessments); count=4,256\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us \n",
"# Dataset Card for 'msmarco-passage/trec-dl-hard'\n\nThe 'msmarco-passage/trec-dl-hard' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=50\n - 'qrels': (relevance assessments); count=4,256\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
0d1c5543ae8c9d7c9a844ca272c1b9794216f7ea |
# Dataset Card for `msmarco-passage/trec-dl-hard/fold1`
The `msmarco-passage/trec-dl-hard/fold1` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/msmarco-passage#msmarco-passage/trec-dl-hard/fold1).
# Data
This dataset provides:
- `queries` (i.e., topics); count=10
- `qrels`: (relevance assessments); count=1,072
- For `docs`, use [`irds/msmarco-passage`](https://huggingface.co/datasets/irds/msmarco-passage)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/msmarco-passage_trec-dl-hard_fold1', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/msmarco-passage_trec-dl-hard_fold1', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Mackie2021DlHard,
title={How Deep is your Learning: the DL-HARD Annotated Deep Learning Dataset},
author={Iain Mackie and Jeffrey Dalton and Andrew Yates},
journal={ArXiv},
year={2021},
volume={abs/2105.07975}
}
@inproceedings{Bajaj2016Msmarco,
title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
author={Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, Tong Wang},
booktitle={InCoCo@NIPS},
year={2016}
}
```
| irds/msmarco-passage_trec-dl-hard_fold1 | [
"task_categories:text-retrieval",
"source_datasets:irds/msmarco-passage",
"region:us"
] | 2023-01-05T03:17:59+00:00 | {"source_datasets": ["irds/msmarco-passage"], "task_categories": ["text-retrieval"], "pretty_name": "`msmarco-passage/trec-dl-hard/fold1`", "viewer": false} | 2023-01-05T03:18:05+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us
|
# Dataset Card for 'msmarco-passage/trec-dl-hard/fold1'
The 'msmarco-passage/trec-dl-hard/fold1' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=10
- 'qrels': (relevance assessments); count=1,072
- For 'docs', use 'irds/msmarco-passage'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'msmarco-passage/trec-dl-hard/fold1'\n\nThe 'msmarco-passage/trec-dl-hard/fold1' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10\n - 'qrels': (relevance assessments); count=1,072\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us \n",
"# Dataset Card for 'msmarco-passage/trec-dl-hard/fold1'\n\nThe 'msmarco-passage/trec-dl-hard/fold1' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10\n - 'qrels': (relevance assessments); count=1,072\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
28f16fc5228f9fb890b1e089ab6c77317c20aef2 |
# Dataset Card for `msmarco-passage/trec-dl-hard/fold2`
The `msmarco-passage/trec-dl-hard/fold2` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/msmarco-passage#msmarco-passage/trec-dl-hard/fold2).
# Data
This dataset provides:
- `queries` (i.e., topics); count=10
- `qrels`: (relevance assessments); count=898
- For `docs`, use [`irds/msmarco-passage`](https://huggingface.co/datasets/irds/msmarco-passage)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/msmarco-passage_trec-dl-hard_fold2', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/msmarco-passage_trec-dl-hard_fold2', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Mackie2021DlHard,
title={How Deep is your Learning: the DL-HARD Annotated Deep Learning Dataset},
author={Iain Mackie and Jeffrey Dalton and Andrew Yates},
journal={ArXiv},
year={2021},
volume={abs/2105.07975}
}
@inproceedings{Bajaj2016Msmarco,
title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
author={Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, Tong Wang},
booktitle={InCoCo@NIPS},
year={2016}
}
```
| irds/msmarco-passage_trec-dl-hard_fold2 | [
"task_categories:text-retrieval",
"source_datasets:irds/msmarco-passage",
"region:us"
] | 2023-01-05T03:18:10+00:00 | {"source_datasets": ["irds/msmarco-passage"], "task_categories": ["text-retrieval"], "pretty_name": "`msmarco-passage/trec-dl-hard/fold2`", "viewer": false} | 2023-01-05T03:18:16+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us
|
# Dataset Card for 'msmarco-passage/trec-dl-hard/fold2'
The 'msmarco-passage/trec-dl-hard/fold2' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=10
- 'qrels': (relevance assessments); count=898
- For 'docs', use 'irds/msmarco-passage'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'msmarco-passage/trec-dl-hard/fold2'\n\nThe 'msmarco-passage/trec-dl-hard/fold2' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10\n - 'qrels': (relevance assessments); count=898\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us \n",
"# Dataset Card for 'msmarco-passage/trec-dl-hard/fold2'\n\nThe 'msmarco-passage/trec-dl-hard/fold2' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10\n - 'qrels': (relevance assessments); count=898\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
9328cd2381826e6c4f4720f1b045ba75a4124f61 |
# Dataset Card for `msmarco-passage/trec-dl-hard/fold3`
The `msmarco-passage/trec-dl-hard/fold3` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/msmarco-passage#msmarco-passage/trec-dl-hard/fold3).
# Data
This dataset provides:
- `queries` (i.e., topics); count=10
- `qrels`: (relevance assessments); count=444
- For `docs`, use [`irds/msmarco-passage`](https://huggingface.co/datasets/irds/msmarco-passage)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/msmarco-passage_trec-dl-hard_fold3', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/msmarco-passage_trec-dl-hard_fold3', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Mackie2021DlHard,
title={How Deep is your Learning: the DL-HARD Annotated Deep Learning Dataset},
author={Iain Mackie and Jeffrey Dalton and Andrew Yates},
journal={ArXiv},
year={2021},
volume={abs/2105.07975}
}
@inproceedings{Bajaj2016Msmarco,
title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
author={Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, Tong Wang},
booktitle={InCoCo@NIPS},
year={2016}
}
```
| irds/msmarco-passage_trec-dl-hard_fold3 | [
"task_categories:text-retrieval",
"source_datasets:irds/msmarco-passage",
"region:us"
] | 2023-01-05T03:18:22+00:00 | {"source_datasets": ["irds/msmarco-passage"], "task_categories": ["text-retrieval"], "pretty_name": "`msmarco-passage/trec-dl-hard/fold3`", "viewer": false} | 2023-01-05T03:18:28+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us
|
# Dataset Card for 'msmarco-passage/trec-dl-hard/fold3'
The 'msmarco-passage/trec-dl-hard/fold3' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=10
- 'qrels': (relevance assessments); count=444
- For 'docs', use 'irds/msmarco-passage'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'msmarco-passage/trec-dl-hard/fold3'\n\nThe 'msmarco-passage/trec-dl-hard/fold3' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10\n - 'qrels': (relevance assessments); count=444\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us \n",
"# Dataset Card for 'msmarco-passage/trec-dl-hard/fold3'\n\nThe 'msmarco-passage/trec-dl-hard/fold3' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10\n - 'qrels': (relevance assessments); count=444\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
e05f315864a95239e4d0b39ce54fdc79b25dffb2 |
# Dataset Card for `msmarco-passage/trec-dl-hard/fold4`
The `msmarco-passage/trec-dl-hard/fold4` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/msmarco-passage#msmarco-passage/trec-dl-hard/fold4).
# Data
This dataset provides:
- `queries` (i.e., topics); count=10
- `qrels`: (relevance assessments); count=716
- For `docs`, use [`irds/msmarco-passage`](https://huggingface.co/datasets/irds/msmarco-passage)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/msmarco-passage_trec-dl-hard_fold4', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/msmarco-passage_trec-dl-hard_fold4', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Mackie2021DlHard,
title={How Deep is your Learning: the DL-HARD Annotated Deep Learning Dataset},
author={Iain Mackie and Jeffrey Dalton and Andrew Yates},
journal={ArXiv},
year={2021},
volume={abs/2105.07975}
}
@inproceedings{Bajaj2016Msmarco,
title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
author={Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, Tong Wang},
booktitle={InCoCo@NIPS},
year={2016}
}
```
| irds/msmarco-passage_trec-dl-hard_fold4 | [
"task_categories:text-retrieval",
"source_datasets:irds/msmarco-passage",
"region:us"
] | 2023-01-05T03:18:33+00:00 | {"source_datasets": ["irds/msmarco-passage"], "task_categories": ["text-retrieval"], "pretty_name": "`msmarco-passage/trec-dl-hard/fold4`", "viewer": false} | 2023-01-05T03:18:39+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us
|
# Dataset Card for 'msmarco-passage/trec-dl-hard/fold4'
The 'msmarco-passage/trec-dl-hard/fold4' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=10
- 'qrels': (relevance assessments); count=716
- For 'docs', use 'irds/msmarco-passage'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'msmarco-passage/trec-dl-hard/fold4'\n\nThe 'msmarco-passage/trec-dl-hard/fold4' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10\n - 'qrels': (relevance assessments); count=716\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us \n",
"# Dataset Card for 'msmarco-passage/trec-dl-hard/fold4'\n\nThe 'msmarco-passage/trec-dl-hard/fold4' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10\n - 'qrels': (relevance assessments); count=716\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
7f96a0dfde501b9cb37db2482b6efbf357a317db |
# Dataset Card for `msmarco-passage/trec-dl-hard/fold5`
The `msmarco-passage/trec-dl-hard/fold5` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/msmarco-passage#msmarco-passage/trec-dl-hard/fold5).
# Data
This dataset provides:
- `queries` (i.e., topics); count=10
- `qrels`: (relevance assessments); count=1,126
- For `docs`, use [`irds/msmarco-passage`](https://huggingface.co/datasets/irds/msmarco-passage)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/msmarco-passage_trec-dl-hard_fold5', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/msmarco-passage_trec-dl-hard_fold5', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Mackie2021DlHard,
title={How Deep is your Learning: the DL-HARD Annotated Deep Learning Dataset},
author={Iain Mackie and Jeffrey Dalton and Andrew Yates},
journal={ArXiv},
year={2021},
volume={abs/2105.07975}
}
@inproceedings{Bajaj2016Msmarco,
title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
author={Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, Tong Wang},
booktitle={InCoCo@NIPS},
year={2016}
}
```
| irds/msmarco-passage_trec-dl-hard_fold5 | [
"task_categories:text-retrieval",
"source_datasets:irds/msmarco-passage",
"region:us"
] | 2023-01-05T03:18:45+00:00 | {"source_datasets": ["irds/msmarco-passage"], "task_categories": ["text-retrieval"], "pretty_name": "`msmarco-passage/trec-dl-hard/fold5`", "viewer": false} | 2023-01-05T03:18:51+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us
|
# Dataset Card for 'msmarco-passage/trec-dl-hard/fold5'
The 'msmarco-passage/trec-dl-hard/fold5' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=10
- 'qrels': (relevance assessments); count=1,126
- For 'docs', use 'irds/msmarco-passage'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'msmarco-passage/trec-dl-hard/fold5'\n\nThe 'msmarco-passage/trec-dl-hard/fold5' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10\n - 'qrels': (relevance assessments); count=1,126\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/msmarco-passage #region-us \n",
"# Dataset Card for 'msmarco-passage/trec-dl-hard/fold5'\n\nThe 'msmarco-passage/trec-dl-hard/fold5' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=10\n - 'qrels': (relevance assessments); count=1,126\n\n - For 'docs', use 'irds/msmarco-passage'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
913b4b74161e8b0da4594bfd2b35d311f93bc461 |
# Dataset Card for `mmarco/de`
The `mmarco/de` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/de).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=8,841,823
This dataset is used by: [`mmarco_de_dev`](https://huggingface.co/datasets/irds/mmarco_de_dev), [`mmarco_de_train`](https://huggingface.co/datasets/irds/mmarco_de_train)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/mmarco_de', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_de | [
"task_categories:text-retrieval",
"region:us"
] | 2023-01-05T03:18:56+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/de`", "viewer": false} | 2023-01-05T03:19:02+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #region-us
|
# Dataset Card for 'mmarco/de'
The 'mmarco/de' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=8,841,823
This dataset is used by: 'mmarco_de_dev', 'mmarco_de_train'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/de'\n\nThe 'mmarco/de' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,841,823\n\n\nThis dataset is used by: 'mmarco_de_dev', 'mmarco_de_train'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #region-us \n",
"# Dataset Card for 'mmarco/de'\n\nThe 'mmarco/de' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,841,823\n\n\nThis dataset is used by: 'mmarco_de_dev', 'mmarco_de_train'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
5318697117a4dd1f182ab0f84c8169d9f77fd8f4 |
# Dataset Card for `mmarco/de/dev`
The `mmarco/de/dev` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/de/dev).
# Data
This dataset provides:
- `queries` (i.e., topics); count=101,093
- `qrels`: (relevance assessments); count=59,273
- For `docs`, use [`irds/mmarco_de`](https://huggingface.co/datasets/irds/mmarco_de)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/mmarco_de_dev', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/mmarco_de_dev', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_de_dev | [
"task_categories:text-retrieval",
"source_datasets:irds/mmarco_de",
"region:us"
] | 2023-01-05T03:19:07+00:00 | {"source_datasets": ["irds/mmarco_de"], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/de/dev`", "viewer": false} | 2023-01-05T03:19:14+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/mmarco_de #region-us
|
# Dataset Card for 'mmarco/de/dev'
The 'mmarco/de/dev' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=101,093
- 'qrels': (relevance assessments); count=59,273
- For 'docs', use 'irds/mmarco_de'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/de/dev'\n\nThe 'mmarco/de/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,093\n - 'qrels': (relevance assessments); count=59,273\n\n - For 'docs', use 'irds/mmarco_de'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/mmarco_de #region-us \n",
"# Dataset Card for 'mmarco/de/dev'\n\nThe 'mmarco/de/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,093\n - 'qrels': (relevance assessments); count=59,273\n\n - For 'docs', use 'irds/mmarco_de'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
39560409ee079e73867791aa2836b00d7b105121 |
# Dataset Card for `mmarco/de/train`
The `mmarco/de/train` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/de/train).
# Data
This dataset provides:
- `queries` (i.e., topics); count=808,731
- `qrels`: (relevance assessments); count=532,761
- `docpairs`; count=39,780,811
- For `docs`, use [`irds/mmarco_de`](https://huggingface.co/datasets/irds/mmarco_de)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/mmarco_de_train', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/mmarco_de_train', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
docpairs = load_dataset('irds/mmarco_de_train', 'docpairs')
for record in docpairs:
record # {'query_id': ..., 'doc_id_a': ..., 'doc_id_b': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_de_train | [
"task_categories:text-retrieval",
"source_datasets:irds/mmarco_de",
"region:us"
] | 2023-01-05T03:19:19+00:00 | {"source_datasets": ["irds/mmarco_de"], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/de/train`", "viewer": false} | 2023-01-05T03:19:25+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/mmarco_de #region-us
|
# Dataset Card for 'mmarco/de/train'
The 'mmarco/de/train' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=808,731
- 'qrels': (relevance assessments); count=532,761
- 'docpairs'; count=39,780,811
- For 'docs', use 'irds/mmarco_de'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/de/train'\n\nThe 'mmarco/de/train' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=808,731\n - 'qrels': (relevance assessments); count=532,761\n - 'docpairs'; count=39,780,811\n\n - For 'docs', use 'irds/mmarco_de'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/mmarco_de #region-us \n",
"# Dataset Card for 'mmarco/de/train'\n\nThe 'mmarco/de/train' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=808,731\n - 'qrels': (relevance assessments); count=532,761\n - 'docpairs'; count=39,780,811\n\n - For 'docs', use 'irds/mmarco_de'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
3e18dee28ad468246a5280b641c1a7f59d2286ac |
# Dataset Card for `mmarco/es`
The `mmarco/es` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/es).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=8,841,823
This dataset is used by: [`mmarco_es_dev`](https://huggingface.co/datasets/irds/mmarco_es_dev), [`mmarco_es_train`](https://huggingface.co/datasets/irds/mmarco_es_train)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/mmarco_es', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_es | [
"task_categories:text-retrieval",
"region:us"
] | 2023-01-05T03:19:31+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/es`", "viewer": false} | 2023-01-05T03:19:37+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #region-us
|
# Dataset Card for 'mmarco/es'
The 'mmarco/es' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=8,841,823
This dataset is used by: 'mmarco_es_dev', 'mmarco_es_train'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/es'\n\nThe 'mmarco/es' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,841,823\n\n\nThis dataset is used by: 'mmarco_es_dev', 'mmarco_es_train'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #region-us \n",
"# Dataset Card for 'mmarco/es'\n\nThe 'mmarco/es' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,841,823\n\n\nThis dataset is used by: 'mmarco_es_dev', 'mmarco_es_train'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
d2ae92f49e7c11f60a7551ad2e4733343daa21c5 |
# Dataset Card for `mmarco/es/dev`
The `mmarco/es/dev` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/es/dev).
# Data
This dataset provides:
- `queries` (i.e., topics); count=101,092
- `qrels`: (relevance assessments); count=59,273
- For `docs`, use [`irds/mmarco_es`](https://huggingface.co/datasets/irds/mmarco_es)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/mmarco_es_dev', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/mmarco_es_dev', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_es_dev | [
"task_categories:text-retrieval",
"source_datasets:irds/mmarco_es",
"region:us"
] | 2023-01-05T03:19:42+00:00 | {"source_datasets": ["irds/mmarco_es"], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/es/dev`", "viewer": false} | 2023-01-05T03:19:48+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/mmarco_es #region-us
|
# Dataset Card for 'mmarco/es/dev'
The 'mmarco/es/dev' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=101,092
- 'qrels': (relevance assessments); count=59,273
- For 'docs', use 'irds/mmarco_es'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/es/dev'\n\nThe 'mmarco/es/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,092\n - 'qrels': (relevance assessments); count=59,273\n\n - For 'docs', use 'irds/mmarco_es'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/mmarco_es #region-us \n",
"# Dataset Card for 'mmarco/es/dev'\n\nThe 'mmarco/es/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,092\n - 'qrels': (relevance assessments); count=59,273\n\n - For 'docs', use 'irds/mmarco_es'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
224ef56d6b405ccf0d1d0b16d72b6cabd078c93d |
# Dataset Card for `mmarco/es/train`
The `mmarco/es/train` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/es/train).
# Data
This dataset provides:
- `queries` (i.e., topics); count=808,731
- `qrels`: (relevance assessments); count=532,761
- `docpairs`; count=39,780,811
- For `docs`, use [`irds/mmarco_es`](https://huggingface.co/datasets/irds/mmarco_es)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/mmarco_es_train', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/mmarco_es_train', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
docpairs = load_dataset('irds/mmarco_es_train', 'docpairs')
for record in docpairs:
record # {'query_id': ..., 'doc_id_a': ..., 'doc_id_b': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_es_train | [
"task_categories:text-retrieval",
"source_datasets:irds/mmarco_es",
"region:us"
] | 2023-01-05T03:19:54+00:00 | {"source_datasets": ["irds/mmarco_es"], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/es/train`", "viewer": false} | 2023-01-05T03:19:59+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/mmarco_es #region-us
|
# Dataset Card for 'mmarco/es/train'
The 'mmarco/es/train' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=808,731
- 'qrels': (relevance assessments); count=532,761
- 'docpairs'; count=39,780,811
- For 'docs', use 'irds/mmarco_es'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/es/train'\n\nThe 'mmarco/es/train' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=808,731\n - 'qrels': (relevance assessments); count=532,761\n - 'docpairs'; count=39,780,811\n\n - For 'docs', use 'irds/mmarco_es'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/mmarco_es #region-us \n",
"# Dataset Card for 'mmarco/es/train'\n\nThe 'mmarco/es/train' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=808,731\n - 'qrels': (relevance assessments); count=532,761\n - 'docpairs'; count=39,780,811\n\n - For 'docs', use 'irds/mmarco_es'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
9be96a7ba7c9b3c875234cc6502e3265e3fca1c4 |
# Dataset Card for `mmarco/fr`
The `mmarco/fr` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/fr).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=8,841,823
This dataset is used by: [`mmarco_fr_dev`](https://huggingface.co/datasets/irds/mmarco_fr_dev), [`mmarco_fr_train`](https://huggingface.co/datasets/irds/mmarco_fr_train)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/mmarco_fr', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_fr | [
"task_categories:text-retrieval",
"region:us"
] | 2023-01-05T03:20:05+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/fr`", "viewer": false} | 2023-01-05T03:20:11+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #region-us
|
# Dataset Card for 'mmarco/fr'
The 'mmarco/fr' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=8,841,823
This dataset is used by: 'mmarco_fr_dev', 'mmarco_fr_train'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/fr'\n\nThe 'mmarco/fr' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,841,823\n\n\nThis dataset is used by: 'mmarco_fr_dev', 'mmarco_fr_train'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #region-us \n",
"# Dataset Card for 'mmarco/fr'\n\nThe 'mmarco/fr' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,841,823\n\n\nThis dataset is used by: 'mmarco_fr_dev', 'mmarco_fr_train'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
8ce34210d36d56a3699310cb6c46887a695dd2bf |
# Dataset Card for `mmarco/fr/dev`
The `mmarco/fr/dev` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/fr/dev).
# Data
This dataset provides:
- `queries` (i.e., topics); count=101,093
- `qrels`: (relevance assessments); count=59,273
- For `docs`, use [`irds/mmarco_fr`](https://huggingface.co/datasets/irds/mmarco_fr)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/mmarco_fr_dev', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/mmarco_fr_dev', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_fr_dev | [
"task_categories:text-retrieval",
"source_datasets:irds/mmarco_fr",
"region:us"
] | 2023-01-05T03:20:16+00:00 | {"source_datasets": ["irds/mmarco_fr"], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/fr/dev`", "viewer": false} | 2023-01-05T03:20:22+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/mmarco_fr #region-us
|
# Dataset Card for 'mmarco/fr/dev'
The 'mmarco/fr/dev' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=101,093
- 'qrels': (relevance assessments); count=59,273
- For 'docs', use 'irds/mmarco_fr'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/fr/dev'\n\nThe 'mmarco/fr/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,093\n - 'qrels': (relevance assessments); count=59,273\n\n - For 'docs', use 'irds/mmarco_fr'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/mmarco_fr #region-us \n",
"# Dataset Card for 'mmarco/fr/dev'\n\nThe 'mmarco/fr/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,093\n - 'qrels': (relevance assessments); count=59,273\n\n - For 'docs', use 'irds/mmarco_fr'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
e1ebd14d7bb66bad1f0c37581ecb3fbc74c89c42 |
# Dataset Card for `mmarco/fr/train`
The `mmarco/fr/train` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/fr/train).
# Data
This dataset provides:
- `queries` (i.e., topics); count=808,731
- `qrels`: (relevance assessments); count=532,761
- `docpairs`; count=39,780,811
- For `docs`, use [`irds/mmarco_fr`](https://huggingface.co/datasets/irds/mmarco_fr)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/mmarco_fr_train', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/mmarco_fr_train', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
docpairs = load_dataset('irds/mmarco_fr_train', 'docpairs')
for record in docpairs:
record # {'query_id': ..., 'doc_id_a': ..., 'doc_id_b': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_fr_train | [
"task_categories:text-retrieval",
"source_datasets:irds/mmarco_fr",
"region:us"
] | 2023-01-05T03:20:28+00:00 | {"source_datasets": ["irds/mmarco_fr"], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/fr/train`", "viewer": false} | 2023-01-05T03:20:35+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/mmarco_fr #region-us
|
# Dataset Card for 'mmarco/fr/train'
The 'mmarco/fr/train' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=808,731
- 'qrels': (relevance assessments); count=532,761
- 'docpairs'; count=39,780,811
- For 'docs', use 'irds/mmarco_fr'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/fr/train'\n\nThe 'mmarco/fr/train' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=808,731\n - 'qrels': (relevance assessments); count=532,761\n - 'docpairs'; count=39,780,811\n\n - For 'docs', use 'irds/mmarco_fr'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/mmarco_fr #region-us \n",
"# Dataset Card for 'mmarco/fr/train'\n\nThe 'mmarco/fr/train' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=808,731\n - 'qrels': (relevance assessments); count=532,761\n - 'docpairs'; count=39,780,811\n\n - For 'docs', use 'irds/mmarco_fr'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
121d66064395028f03b0c2eb1c2e78a71d8d5772 |
# Dataset Card for `mmarco/id`
The `mmarco/id` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/id).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=8,841,823
This dataset is used by: [`mmarco_id_dev`](https://huggingface.co/datasets/irds/mmarco_id_dev), [`mmarco_id_train`](https://huggingface.co/datasets/irds/mmarco_id_train)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/mmarco_id', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_id | [
"task_categories:text-retrieval",
"region:us"
] | 2023-01-05T03:20:40+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/id`", "viewer": false} | 2023-01-05T03:20:46+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #region-us
|
# Dataset Card for 'mmarco/id'
The 'mmarco/id' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=8,841,823
This dataset is used by: 'mmarco_id_dev', 'mmarco_id_train'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/id'\n\nThe 'mmarco/id' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,841,823\n\n\nThis dataset is used by: 'mmarco_id_dev', 'mmarco_id_train'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #region-us \n",
"# Dataset Card for 'mmarco/id'\n\nThe 'mmarco/id' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,841,823\n\n\nThis dataset is used by: 'mmarco_id_dev', 'mmarco_id_train'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
a024cb2ae75bbcd0fa6c3cac7fb14ebcf1f5e206 |
# Dataset Card for `mmarco/id/dev`
The `mmarco/id/dev` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/id/dev).
# Data
This dataset provides:
- `queries` (i.e., topics); count=101,093
- `qrels`: (relevance assessments); count=59,273
- For `docs`, use [`irds/mmarco_id`](https://huggingface.co/datasets/irds/mmarco_id)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/mmarco_id_dev', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/mmarco_id_dev', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_id_dev | [
"task_categories:text-retrieval",
"source_datasets:irds/mmarco_id",
"region:us"
] | 2023-01-05T03:20:51+00:00 | {"source_datasets": ["irds/mmarco_id"], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/id/dev`", "viewer": false} | 2023-01-05T03:20:57+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/mmarco_id #region-us
|
# Dataset Card for 'mmarco/id/dev'
The 'mmarco/id/dev' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=101,093
- 'qrels': (relevance assessments); count=59,273
- For 'docs', use 'irds/mmarco_id'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/id/dev'\n\nThe 'mmarco/id/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,093\n - 'qrels': (relevance assessments); count=59,273\n\n - For 'docs', use 'irds/mmarco_id'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/mmarco_id #region-us \n",
"# Dataset Card for 'mmarco/id/dev'\n\nThe 'mmarco/id/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,093\n - 'qrels': (relevance assessments); count=59,273\n\n - For 'docs', use 'irds/mmarco_id'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
8ed13a03e20df3f825e3819af6924db5ffdeb207 |
# Dataset Card for `mmarco/id/train`
The `mmarco/id/train` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/id/train).
# Data
This dataset provides:
- `queries` (i.e., topics); count=808,731
- `qrels`: (relevance assessments); count=532,761
- `docpairs`; count=39,780,811
- For `docs`, use [`irds/mmarco_id`](https://huggingface.co/datasets/irds/mmarco_id)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/mmarco_id_train', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/mmarco_id_train', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
docpairs = load_dataset('irds/mmarco_id_train', 'docpairs')
for record in docpairs:
record # {'query_id': ..., 'doc_id_a': ..., 'doc_id_b': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_id_train | [
"task_categories:text-retrieval",
"source_datasets:irds/mmarco_id",
"region:us"
] | 2023-01-05T03:21:03+00:00 | {"source_datasets": ["irds/mmarco_id"], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/id/train`", "viewer": false} | 2023-01-05T03:21:09+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/mmarco_id #region-us
|
# Dataset Card for 'mmarco/id/train'
The 'mmarco/id/train' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=808,731
- 'qrels': (relevance assessments); count=532,761
- 'docpairs'; count=39,780,811
- For 'docs', use 'irds/mmarco_id'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/id/train'\n\nThe 'mmarco/id/train' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=808,731\n - 'qrels': (relevance assessments); count=532,761\n - 'docpairs'; count=39,780,811\n\n - For 'docs', use 'irds/mmarco_id'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/mmarco_id #region-us \n",
"# Dataset Card for 'mmarco/id/train'\n\nThe 'mmarco/id/train' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=808,731\n - 'qrels': (relevance assessments); count=532,761\n - 'docpairs'; count=39,780,811\n\n - For 'docs', use 'irds/mmarco_id'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
6911b71cabc9c941677f0b6f2ff11d36c0cc897b |
# Dataset Card for `mmarco/it`
The `mmarco/it` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/it).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=8,841,823
This dataset is used by: [`mmarco_it_dev`](https://huggingface.co/datasets/irds/mmarco_it_dev), [`mmarco_it_train`](https://huggingface.co/datasets/irds/mmarco_it_train)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/mmarco_it', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_it | [
"task_categories:text-retrieval",
"region:us"
] | 2023-01-05T03:21:14+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/it`", "viewer": false} | 2023-01-05T03:21:20+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #region-us
|
# Dataset Card for 'mmarco/it'
The 'mmarco/it' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=8,841,823
This dataset is used by: 'mmarco_it_dev', 'mmarco_it_train'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/it'\n\nThe 'mmarco/it' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,841,823\n\n\nThis dataset is used by: 'mmarco_it_dev', 'mmarco_it_train'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #region-us \n",
"# Dataset Card for 'mmarco/it'\n\nThe 'mmarco/it' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,841,823\n\n\nThis dataset is used by: 'mmarco_it_dev', 'mmarco_it_train'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
9041a86a6faf53429176be84cb19064891334ed5 |
# Dataset Card for `mmarco/it/dev`
The `mmarco/it/dev` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/it/dev).
# Data
This dataset provides:
- `queries` (i.e., topics); count=101,093
- `qrels`: (relevance assessments); count=59,273
- For `docs`, use [`irds/mmarco_it`](https://huggingface.co/datasets/irds/mmarco_it)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/mmarco_it_dev', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/mmarco_it_dev', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_it_dev | [
"task_categories:text-retrieval",
"source_datasets:irds/mmarco_it",
"region:us"
] | 2023-01-05T03:21:25+00:00 | {"source_datasets": ["irds/mmarco_it"], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/it/dev`", "viewer": false} | 2023-01-05T03:21:31+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/mmarco_it #region-us
|
# Dataset Card for 'mmarco/it/dev'
The 'mmarco/it/dev' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=101,093
- 'qrels': (relevance assessments); count=59,273
- For 'docs', use 'irds/mmarco_it'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/it/dev'\n\nThe 'mmarco/it/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,093\n - 'qrels': (relevance assessments); count=59,273\n\n - For 'docs', use 'irds/mmarco_it'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/mmarco_it #region-us \n",
"# Dataset Card for 'mmarco/it/dev'\n\nThe 'mmarco/it/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,093\n - 'qrels': (relevance assessments); count=59,273\n\n - For 'docs', use 'irds/mmarco_it'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
ed816a1fc65c82f46a2cd1eb029e7432d4032c13 |
# Dataset Card for `mmarco/it/train`
The `mmarco/it/train` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/it/train).
# Data
This dataset provides:
- `queries` (i.e., topics); count=808,731
- `qrels`: (relevance assessments); count=532,761
- `docpairs`; count=39,780,811
- For `docs`, use [`irds/mmarco_it`](https://huggingface.co/datasets/irds/mmarco_it)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/mmarco_it_train', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/mmarco_it_train', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
docpairs = load_dataset('irds/mmarco_it_train', 'docpairs')
for record in docpairs:
record # {'query_id': ..., 'doc_id_a': ..., 'doc_id_b': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_it_train | [
"task_categories:text-retrieval",
"source_datasets:irds/mmarco_it",
"region:us"
] | 2023-01-05T03:21:37+00:00 | {"source_datasets": ["irds/mmarco_it"], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/it/train`", "viewer": false} | 2023-01-05T03:21:42+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/mmarco_it #region-us
|
# Dataset Card for 'mmarco/it/train'
The 'mmarco/it/train' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=808,731
- 'qrels': (relevance assessments); count=532,761
- 'docpairs'; count=39,780,811
- For 'docs', use 'irds/mmarco_it'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/it/train'\n\nThe 'mmarco/it/train' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=808,731\n - 'qrels': (relevance assessments); count=532,761\n - 'docpairs'; count=39,780,811\n\n - For 'docs', use 'irds/mmarco_it'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/mmarco_it #region-us \n",
"# Dataset Card for 'mmarco/it/train'\n\nThe 'mmarco/it/train' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=808,731\n - 'qrels': (relevance assessments); count=532,761\n - 'docpairs'; count=39,780,811\n\n - For 'docs', use 'irds/mmarco_it'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
0d5b98409b96ddb651dd383b19a955fd285ba41c |
# Dataset Card for `mmarco/pt`
The `mmarco/pt` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/pt).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=8,841,823
This dataset is used by: [`mmarco_pt_dev`](https://huggingface.co/datasets/irds/mmarco_pt_dev), [`mmarco_pt_dev_small`](https://huggingface.co/datasets/irds/mmarco_pt_dev_small), [`mmarco_pt_dev_v1.1`](https://huggingface.co/datasets/irds/mmarco_pt_dev_v1.1), [`mmarco_pt_train`](https://huggingface.co/datasets/irds/mmarco_pt_train), [`mmarco_pt_train_v1.1`](https://huggingface.co/datasets/irds/mmarco_pt_train_v1.1)
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/mmarco_pt', 'docs')
for record in docs:
record # {'doc_id': ..., 'text': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_pt | [
"task_categories:text-retrieval",
"region:us"
] | 2023-01-05T03:21:48+00:00 | {"source_datasets": [], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/pt`", "viewer": false} | 2023-01-05T03:21:53+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #region-us
|
# Dataset Card for 'mmarco/pt'
The 'mmarco/pt' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'docs' (documents, i.e., the corpus); count=8,841,823
This dataset is used by: 'mmarco_pt_dev', 'mmarco_pt_dev_small', 'mmarco_pt_dev_v1.1', 'mmarco_pt_train', 'mmarco_pt_train_v1.1'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/pt'\n\nThe 'mmarco/pt' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,841,823\n\n\nThis dataset is used by: 'mmarco_pt_dev', 'mmarco_pt_dev_small', 'mmarco_pt_dev_v1.1', 'mmarco_pt_train', 'mmarco_pt_train_v1.1'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #region-us \n",
"# Dataset Card for 'mmarco/pt'\n\nThe 'mmarco/pt' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'docs' (documents, i.e., the corpus); count=8,841,823\n\n\nThis dataset is used by: 'mmarco_pt_dev', 'mmarco_pt_dev_small', 'mmarco_pt_dev_v1.1', 'mmarco_pt_train', 'mmarco_pt_train_v1.1'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
fd0b5ecc91d7554363318d22452441ace17ef00a |
# Dataset Card for `mmarco/pt/dev`
The `mmarco/pt/dev` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/pt/dev).
# Data
This dataset provides:
- `queries` (i.e., topics); count=101,619
- `qrels`: (relevance assessments); count=59,273
- For `docs`, use [`irds/mmarco_pt`](https://huggingface.co/datasets/irds/mmarco_pt)
This dataset is used by: [`mmarco_pt_dev_v1.1`](https://huggingface.co/datasets/irds/mmarco_pt_dev_v1.1)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/mmarco_pt_dev', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/mmarco_pt_dev', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_pt_dev | [
"task_categories:text-retrieval",
"source_datasets:irds/mmarco_pt",
"region:us"
] | 2023-01-05T03:21:59+00:00 | {"source_datasets": ["irds/mmarco_pt"], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/pt/dev`", "viewer": false} | 2023-01-05T03:22:05+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/mmarco_pt #region-us
|
# Dataset Card for 'mmarco/pt/dev'
The 'mmarco/pt/dev' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=101,619
- 'qrels': (relevance assessments); count=59,273
- For 'docs', use 'irds/mmarco_pt'
This dataset is used by: 'mmarco_pt_dev_v1.1'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/pt/dev'\n\nThe 'mmarco/pt/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,619\n - 'qrels': (relevance assessments); count=59,273\n\n - For 'docs', use 'irds/mmarco_pt'\n\nThis dataset is used by: 'mmarco_pt_dev_v1.1'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/mmarco_pt #region-us \n",
"# Dataset Card for 'mmarco/pt/dev'\n\nThe 'mmarco/pt/dev' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=101,619\n - 'qrels': (relevance assessments); count=59,273\n\n - For 'docs', use 'irds/mmarco_pt'\n\nThis dataset is used by: 'mmarco_pt_dev_v1.1'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
dc6503ba07a3359edd9d8f8721cb2ea7b4513a6d |
# Dataset Card for `mmarco/pt/dev/small`
The `mmarco/pt/dev/small` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/pt/dev/small).
# Data
This dataset provides:
- `queries` (i.e., topics); count=7,000
- `qrels`: (relevance assessments); count=7,437
- For `docs`, use [`irds/mmarco_pt`](https://huggingface.co/datasets/irds/mmarco_pt)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/mmarco_pt_dev_small', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/mmarco_pt_dev_small', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```
| irds/mmarco_pt_dev_small | [
"task_categories:text-retrieval",
"source_datasets:irds/mmarco_pt",
"region:us"
] | 2023-01-05T03:22:10+00:00 | {"source_datasets": ["irds/mmarco_pt"], "task_categories": ["text-retrieval"], "pretty_name": "`mmarco/pt/dev/small`", "viewer": false} | 2023-01-05T03:22:16+00:00 | [] | [] | TAGS
#task_categories-text-retrieval #source_datasets-irds/mmarco_pt #region-us
|
# Dataset Card for 'mmarco/pt/dev/small'
The 'mmarco/pt/dev/small' dataset, provided by the ir-datasets package.
For more information about the dataset, see the documentation.
# Data
This dataset provides:
- 'queries' (i.e., topics); count=7,000
- 'qrels': (relevance assessments); count=7,437
- For 'docs', use 'irds/mmarco_pt'
## Usage
Note that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in Dataset format.
| [
"# Dataset Card for 'mmarco/pt/dev/small'\n\nThe 'mmarco/pt/dev/small' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=7,000\n - 'qrels': (relevance assessments); count=7,437\n\n - For 'docs', use 'irds/mmarco_pt'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] | [
"TAGS\n#task_categories-text-retrieval #source_datasets-irds/mmarco_pt #region-us \n",
"# Dataset Card for 'mmarco/pt/dev/small'\n\nThe 'mmarco/pt/dev/small' dataset, provided by the ir-datasets package.\nFor more information about the dataset, see the documentation.",
"# Data\n\nThis dataset provides:\n - 'queries' (i.e., topics); count=7,000\n - 'qrels': (relevance assessments); count=7,437\n\n - For 'docs', use 'irds/mmarco_pt'",
"## Usage\n\n\n\nNote that calling 'load_dataset' will download the dataset (or provide access instructions when it's not public) and make a copy of the\ndata in Dataset format."
] |
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