mirror of https://github.com/explosion/spaCy.git
44 lines
1.2 KiB
Python
44 lines
1.2 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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"""
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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 noun 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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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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