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Improve matcher example (resolves #3287)
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@ -306,28 +306,29 @@ match on the uppercase versions, in case someone has written it as "Google i/o".
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### {executable="true"}
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import spacy
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from spacy.matcher import Matcher
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from spacy.tokens import Span
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nlp = spacy.load("en_core_web_sm")
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matcher = Matcher(nlp.vocab)
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# Get the ID of the 'EVENT' entity type. This is required to set an entity.
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EVENT = nlp.vocab.strings["EVENT"]
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def add_event_ent(matcher, doc, i, matches):
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# Get the current match and create tuple of entity label, start and end.
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# Append entity to the doc's entity. (Don't overwrite doc.ents!)
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match_id, start, end = matches[i]
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entity = (EVENT, start, end)
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entity = Span(doc, start, end, label="EVENT")
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doc.ents += (entity,)
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print(doc[start:end].text, entity)
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print(entity.text)
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matcher.add("GoogleIO", add_event_ent,
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[{"ORTH": "Google"}, {"ORTH": "I"}, {"ORTH": "/"}, {"ORTH": "O"}],
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[{"ORTH": "Google"}, {"ORTH": "I"}, {"ORTH": "/"}, {"ORTH": "O"}, {"IS_DIGIT": True}],)
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doc = nlp(u"This is a text about Google I/O 2015.")
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pattern = [{"ORTH": "Google"}, {"ORTH": "I"}, {"ORTH": "/"}, {"ORTH": "O"}]
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matcher.add("GoogleIO", add_event_ent, pattern)
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doc = nlp(u"This is a text about Google I/O.")
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matches = matcher(doc)
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```
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A very similar logic has been implemented in the built-in
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[`EntityRuler`](/api/entityruler) by the way. It also takes care of handling
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overlapping matches, which you would otherwise have to take care of yourself.
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> #### Tip: Visualizing matches
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>
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> When working with entities, you can use [displaCy](/api/top-level#displacy) to
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