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83 lines
2.4 KiB
Python
83 lines
2.4 KiB
Python
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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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# print(prec, rec, intersected)
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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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