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39 lines
1.3 KiB
Plaintext
39 lines
1.3 KiB
Plaintext
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//- 💫 DOCS > USAGE > CUSTOMIZING THE PIPELINE
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include ../../_includes/_mixins
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p
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| spaCy provides several linguistic annotation functions by default. Each
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| function takes a Doc object, and modifies it in-place. The default
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| pipeline is #[code [nlp.tagger, nlp.entity, nlp.parser]]. spaCy 1.0
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| introduced the ability to customise this pipeline with arbitrary
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| functions.
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+code.
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def arbitrary_fixup_rules(doc):
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for token in doc:
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if token.text == u'bill' and token.tag_ == u'NNP':
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token.tag_ = u'NN'
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def custom_pipeline(nlp):
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return (nlp.tagger, arbitrary_fixup_rules, nlp.parser, nlp.entity)
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nlp = spacy.load('en', create_pipeline=custom_pipeline)
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p
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| The easiest way to customise the pipeline is to pass a
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| #[code create_pipeline] callback to the #[code spacy.load()] function.
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p
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| The callback you pass to #[code create_pipeline] should take a single
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| argument, and return a sequence of callables. Each callable in the
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| sequence should accept a #[code Doc] object and modify it in place.
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p
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| Instead of passing a callback, you can also write to the
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| #[code .pipeline] attribute directly.
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+code.
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nlp = spacy.load('en')
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nlp.pipeline = [nlp.tagger]
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