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296446a1c8
<!--- Provide a general summary of your changes in the title. --> ## Description * tidy up and adjust Cython code to code style * improve docstrings and make calling `help()` nicer * add URLs to new docs pages to docstrings wherever possible, mostly to user-facing objects * fix various typos and inconsistencies in docs ### Types of change enhancement, docs ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
56 lines
1.6 KiB
Python
56 lines
1.6 KiB
Python
# coding: utf8
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from __future__ import unicode_literals
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from ..matcher import Matcher
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def merge_noun_chunks(doc):
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"""Merge noun chunks into a single token.
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doc (Doc): The Doc object.
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RETURNS (Doc): The Doc object with merged noun chunks.
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DOCS: https://spacy.io/api/pipeline-functions#merge_noun_chunks
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"""
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if not doc.is_parsed:
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return doc
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with doc.retokenize() as retokenizer:
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for np in doc.noun_chunks:
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attrs = {"tag": np.root.tag, "dep": np.root.dep}
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retokenizer.merge(np, attrs=attrs)
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return doc
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def merge_entities(doc):
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"""Merge entities into a single token.
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doc (Doc): The Doc object.
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RETURNS (Doc): The Doc object with merged entities.
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DOCS: https://spacy.io/api/pipeline-functions#merge_entities
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"""
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with doc.retokenize() as retokenizer:
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for ent in doc.ents:
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attrs = {"tag": ent.root.tag, "dep": ent.root.dep, "ent_type": ent.label}
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retokenizer.merge(ent, attrs=attrs)
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return doc
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def merge_subtokens(doc, label="subtok"):
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"""Merge subtokens into a single token.
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doc (Doc): The Doc object.
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label (unicode): The subtoken dependency label.
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RETURNS (Doc): The Doc object with merged subtokens.
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DOCS: https://spacy.io/api/pipeline-functions#merge_subtokens
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"""
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merger = Matcher(doc.vocab)
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merger.add("SUBTOK", None, [{"DEP": label, "op": "+"}])
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matches = merger(doc)
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spans = [doc[start : end + 1] for _, start, end in matches]
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with doc.retokenize() as retokenizer:
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for span in spans:
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retokenizer.merge(span)
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return doc
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