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The `Matcher` in `merge_subtokens()` returns all possible subsequences of `subtok`, so for sequences of two or more subtoks it's necessary to filter the matches so that the retokenizer is only merging the longest matches with no overlapping spans.
69 lines
2.0 KiB
Python
69 lines
2.0 KiB
Python
# coding: utf8
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from __future__ import unicode_literals
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from ..language import component
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from ..matcher import Matcher
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from ..util import filter_spans
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@component(
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"merge_noun_chunks",
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requires=["token.dep", "token.tag", "token.pos"],
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retokenizes=True,
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)
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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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@component(
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"merge_entities",
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requires=["doc.ents", "token.ent_iob", "token.ent_type"],
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retokenizes=True,
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)
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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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@component("merge_subtokens", requires=["token.dep"], retokenizes=True)
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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 = filter_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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