mirror of https://github.com/explosion/spaCy.git
58 lines
2.2 KiB
Python
58 lines
2.2 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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from ...errors import Errors
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def noun_chunks(doclike):
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"""
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Detect base noun phrases. Works on both Doc and Span.
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"""
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# It follows the logic of the noun chunks finder of English language,
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# adjusted to some Greek language special characteristics.
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# obj tag corrects some DEP tagger mistakes.
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# Further improvement of the models will eliminate the need for this tag.
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labels = ["nsubj", "obj", "iobj", "appos", "ROOT", "obl"]
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doc = doclike.doc # Ensure works on both Doc and Span.
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if not doc.is_parsed:
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raise ValueError(Errors.E029)
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np_deps = [doc.vocab.strings.add(label) for label in labels]
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conj = doc.vocab.strings.add("conj")
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nmod = doc.vocab.strings.add("nmod")
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np_label = doc.vocab.strings.add("NP")
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prev_end = -1
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for i, word in enumerate(doclike):
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if word.pos not in (NOUN, PROPN, PRON):
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continue
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# Prevent nested chunks from being produced
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if word.left_edge.i <= prev_end:
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continue
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if word.dep in np_deps:
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flag = False
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if word.pos == NOUN:
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# check for patterns such as γραμμή παραγωγής
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for potential_nmod in word.rights:
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if potential_nmod.dep == nmod:
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prev_end = potential_nmod.i + 1
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yield word.left_edge.i, potential_nmod.i + 1, np_label
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flag = True
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break
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if flag is False:
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prev_end = word.i + 1
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yield word.left_edge.i, word.i + 1, np_label
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elif word.dep == conj:
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# covers the case: έχει όμορφα και έξυπνα παιδιά
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head = word.head
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while head.dep == conj and head.head.i < head.i:
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head = head.head
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# If the head is an NP, and we're coordinated to it, we're an NP
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if head.dep in np_deps:
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prev_end = word.i + 1
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yield word.left_edge.i, word.i + 1, np_label
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SYNTAX_ITERATORS = {"noun_chunks": noun_chunks}
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