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e649242927
* Prevent overlapping noun chunks in Spanish noun chunk iterator * Clean up similar code in Danish noun chunk iterator
75 lines
2.0 KiB
Python
75 lines
2.0 KiB
Python
# coding: utf8
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from __future__ import unicode_literals
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from ...symbols import NOUN, PROPN, PRON, VERB, AUX
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from ...errors import Errors
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def noun_chunks(doclike):
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def is_verb_token(tok):
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return tok.pos in [VERB, AUX]
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def get_left_bound(doc, root):
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left_bound = root
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for tok in reversed(list(root.lefts)):
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if tok.dep in np_left_deps:
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left_bound = tok
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return left_bound
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def get_right_bound(doc, root):
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right_bound = root
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for tok in root.rights:
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if tok.dep in np_right_deps:
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right = get_right_bound(doc, tok)
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if list(
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filter(
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lambda t: is_verb_token(t) or t.dep in stop_deps,
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doc[root.i : right.i],
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)
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):
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break
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else:
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right_bound = right
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return right_bound
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def get_bounds(doc, root):
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return get_left_bound(doc, root), get_right_bound(doc, root)
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doc = doclike.doc
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if not doc.is_parsed:
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raise ValueError(Errors.E029)
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if not len(doc):
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return
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left_labels = [
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"det",
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"fixed",
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"nmod:poss",
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"amod",
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"flat",
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"goeswith",
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"nummod",
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"appos",
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]
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right_labels = ["fixed", "nmod:poss", "amod", "flat", "goeswith", "nummod", "appos"]
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stop_labels = ["punct"]
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np_label = doc.vocab.strings.add("NP")
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np_left_deps = [doc.vocab.strings.add(label) for label in left_labels]
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np_right_deps = [doc.vocab.strings.add(label) for label in right_labels]
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stop_deps = [doc.vocab.strings.add(label) for label in stop_labels]
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prev_right = -1
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for token in doclike:
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if token.pos in [PROPN, NOUN, PRON]:
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left, right = get_bounds(doc, token)
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if left.i <= prev_right:
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continue
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yield left.i, right.i + 1, np_label
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prev_right = right.i
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SYNTAX_ITERATORS = {"noun_chunks": noun_chunks}
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