Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
< 1K
License:
Update README.md
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README.md
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# License
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cc-by-nc-4.0
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---
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# CaseReportBench: Clinical Dense Extraction Benchmark
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**CaseReportBench** is a curated benchmark dataset designed to evaluate the ability of large language models to perform **dense information extraction** from **clinical case reports**, particularly in the context of **rare disease diagnosis**.
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booktitle={Conference on Health, Inference, and Learning (CHIL)},
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year={2025}
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}
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```
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---
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annotations_creators:
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- expert-generated
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language:
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- en
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license: cc-by-nc-4.0
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multilinguality: monolingual
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pretty_name: CaseReportBench - Clinical Dense Extraction Benchmark
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tags:
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- clinical-nlp
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- dense-information-extraction
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- medical
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- case-reports
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- rare-diseases
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- benchmarking
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- information-extraction
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task_categories:
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- information-extraction
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- text-classification
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- question-answering
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task_ids:
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- entity-extraction
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- multi-label-classification
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- open-domain-qa
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---
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# CaseReportBench: Clinical Dense Extraction Benchmark
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**CaseReportBench** is a curated benchmark dataset designed to evaluate the ability of large language models to perform **dense information extraction** from **clinical case reports**, particularly in the context of **rare disease diagnosis**.
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booktitle={Conference on Health, Inference, and Learning (CHIL)},
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year={2025}
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}
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```
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