mirror of https://github.com/explosion/spaCy.git
39 lines
1.4 KiB
Python
39 lines
1.4 KiB
Python
# coding: utf8
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from __future__ import unicode_literals
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from ...symbols import NOUN, PROPN, PRON
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def noun_chunks(obj):
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"""
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Detect base noun phrases from a dependency parse. Works on both Doc and Span.
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"""
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# this iterator extracts spans headed by NOUNs starting from the left-most
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# syntactic dependent until the NOUN itself for close apposition and
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# measurement construction, the span is sometimes extended to the right of
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# the NOUN. Example: "eine Tasse Tee" (a cup (of) tea) returns "eine Tasse Tee"
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# and not just "eine Tasse", same for "das Thema Familie".
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labels = ['sb', 'oa', 'da', 'nk', 'mo', 'ag', 'ROOT', 'root', 'cj', 'pd', 'og', 'app']
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doc = obj.doc # Ensure works on both Doc and Span.
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np_label = doc.vocab.strings.add('NP')
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np_deps = set(doc.vocab.strings.add(label) for label in labels)
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close_app = doc.vocab.strings.add('nk')
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rbracket = 0
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for i, word in enumerate(obj):
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if i < rbracket:
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continue
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if word.pos in (NOUN, PROPN, PRON) and word.dep in np_deps:
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rbracket = word.i+1
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# try to extend the span to the right
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# to capture close apposition/measurement constructions
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for rdep in doc[word.i].rights:
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if rdep.pos in (NOUN, PROPN) and rdep.dep == close_app:
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rbracket = rdep.i+1
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yield word.left_edge.i, rbracket, np_label
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SYNTAX_ITERATORS = {
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'noun_chunks': noun_chunks
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}
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