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	Work on test for #615
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							|  | @ -0,0 +1,36 @@ | |||
| from __future__ import unicode_literals | ||||
| import spacy  | ||||
| from spacy.attrs import ORTH | ||||
| 
 | ||||
| 
 | ||||
| def merge_phrases(matcher, doc, i, matches): | ||||
|     ''' | ||||
|     Merge a phrase. We have to be careful here because we'll change the token indices. | ||||
|     To avoid problems, merge all the phrases once we're called on the last match. | ||||
|     ''' | ||||
|     if i != len(matches)-1: | ||||
|         return None | ||||
|     # Get Span objects | ||||
|     spans = [(ent_id, label, doc[start : end]) for ent_id, label, start, end in matches] | ||||
|     for ent_id, label, span in spans: | ||||
|         span.merge('NNP' if label else span.root.tag_, span.text, doc.vocab.strings[label]) | ||||
| 
 | ||||
| def test_entity_ID_assignment(): | ||||
|     nlp = spacy.en.English() | ||||
|     text = u"""The golf club is broken""" | ||||
|     doc = nlp(text) | ||||
| 
 | ||||
|     golf_pattern =     [  | ||||
|             { ORTH: "golf"}, | ||||
|             { ORTH: "club"} | ||||
|         ] | ||||
| 
 | ||||
|     matcher = spacy.matcher.Matcher(nlp.vocab) | ||||
|     matcher.add_entity('Sport_Equipment', on_match = merge_phrases) | ||||
|     matcher.add_pattern("Sport_Equipment", golf_pattern, label = 'Sport_Equipment') | ||||
| 
 | ||||
|     match = matcher(doc) | ||||
|     entities = list(doc.ents) | ||||
| 
 | ||||
|     assert entities != [] #assertion 1 | ||||
|     assert entities[0].label != 0 #assertion 2 | ||||
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