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34 lines
1.1 KiB
Python
34 lines
1.1 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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from ...matcher import Matcher
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def test_issue615(en_tokenizer):
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def merge_phrases(matcher, doc, i, matches):
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"""Merge a phrase. We have to be careful here because we'll change the
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token indices. To avoid problems, merge all the phrases once we're called
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on the last match."""
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if i != len(matches)-1:
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return None
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# Get Span objects
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spans = [(ent_id, ent_id, doc[start : end]) for ent_id, start, end in matches]
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for ent_id, label, span in spans:
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span.merge(tag='NNP' if label else span.root.tag_, lemma=span.text,
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label=label)
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doc.ents = doc.ents + ((label, span.start, span.end),)
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text = "The golf club is broken"
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pattern = [{'ORTH': "golf"}, {'ORTH': "club"}]
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label = "Sport_Equipment"
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doc = en_tokenizer(text)
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matcher = Matcher(doc.vocab)
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matcher.add(label, merge_phrases, pattern)
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match = matcher(doc)
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entities = list(doc.ents)
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assert entities != [] #assertion 1
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assert entities[0].label != 0 #assertion 2
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