spaCy/website/docs/usage/customizing-pipeline.jade

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2016-10-31 21:04:15 +03:00
//- 💫 DOCS > USAGE > CUSTOMIZING THE PIPELINE
include ../../_includes/_mixins
p
| spaCy provides several linguistic annotation functions by default. Each
| function takes a Doc object, and modifies it in-place. The default
| pipeline is #[code [nlp.tagger, nlp.entity, nlp.parser]]. spaCy 1.0
| introduced the ability to customise this pipeline with arbitrary
| functions.
+code.
def arbitrary_fixup_rules(doc):
for token in doc:
if token.text == u'bill' and token.tag_ == u'NNP':
token.tag_ = u'NN'
def custom_pipeline(nlp):
return (nlp.tagger, arbitrary_fixup_rules, nlp.parser, nlp.entity)
nlp = spacy.load('en', create_pipeline=custom_pipeline)
p
| The easiest way to customise the pipeline is to pass a
| #[code create_pipeline] callback to the #[code spacy.load()] function.
p
| The callback you pass to #[code create_pipeline] should take a single
| argument, and return a sequence of callables. Each callable in the
| sequence should accept a #[code Doc] object and modify it in place.
p
| Instead of passing a callback, you can also write to the
| #[code .pipeline] attribute directly.
+code.
nlp = spacy.load('en')
nlp.pipeline = [nlp.tagger]