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import re |
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from ..utils.rc_f1 import CJRCEvaluator |
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""" |
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given a target substring. find its all occurances in the string s |
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return the starting and ending index of every occurance |
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""" |
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def __find_substring_starts(s, target): |
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return [(m.start(), m.end()) for m in re.finditer(target, s)] |
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""" |
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compute the reading comprehension F1 scores |
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hyps and refs are lists of hyposisis and reference strings |
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""" |
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def compute_rc_f1(hyps, refs): |
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scores = 0 |
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for h, r in zip(hyps, refs): |
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scores += CJRCEvaluator.compute_f1(r, h) |
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return {'score': scores / len(hyps)} |
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""" |
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compute the information extraction F1 scores |
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hyps and refs are lists of hyposisis and reference strings |
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entity_types: a set of all possible entity types |
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""" |
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def compute_ie_f1(hyps, refs, entity_types): |
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assert (len(hyps) == len(refs)) |
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scores, abstentions = 0, 0 |
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for h, r in zip(hyps, refs): |
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h = __extract_entities_pred(h, entity_types) |
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r = __extract_entities_ref(r) |
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if r == {}: |
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scores += 1 if h == {} else 0 |
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continue |
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if h == {}: |
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abstentions += 1 |
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intersected = [CJRCEvaluator.compute_f1(r[etype], einstance) for etype, einstance in h.items() if etype in r] |
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prec = sum(intersected) / len(h) if len(h) > 0 else 0 |
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rec = sum(intersected) / len(r) if len(r) > 0 else 0 |
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scores += 2 * prec * rec / (prec + rec + 1e-10) |
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return {'score': scores / len(hyps), "anstention_rate": abstentions / len(hyps)} |
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def __extract_entities_ref(ref): |
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outputs = {} |
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if ref.strip() == '': |
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return outputs |
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for seg in ref.split(';'): |
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seg = seg.split(':') |
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outputs[seg[0]] = seg[1] |
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return outputs |
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""" |
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extract entity type and instances from the model prediction |
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pred: string of model prediction |
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entity_types: a set of all possible entity types |
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""" |
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def __extract_entities_pred(pred, entity_types): |
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outputs = {} |
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for etype in entity_types: |
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occurances = __find_substring_starts(pred, etype) |
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for start, end in occurances: |
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if end >= (len(pred) - 2): |
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continue |
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if pred[end] == ":" or pred[end] == "：": |
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einstance = re.split("\n| ", pred[end + 1:].strip())[0].strip() |
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if einstance != '无' and einstance != '未提及': |
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outputs[etype] = einstance |
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return outputs |
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