spaCy/spacy/lang/es/syntax_iterators.py

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from ...symbols import NOUN, PROPN, PRON, VERB, AUX
from ...errors import Errors
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def noun_chunks(doclike):
doc = doclike.doc
if not doc.is_parsed:
raise ValueError(Errors.E029)
if not len(doc):
return
np_label = doc.vocab.strings.add("NP")
left_labels = ["det", "fixed", "neg"] # ['nunmod', 'det', 'appos', 'fixed']
right_labels = ["flat", "fixed", "compound", "neg"]
stop_labels = ["punct"]
np_left_deps = [doc.vocab.strings.add(label) for label in left_labels]
np_right_deps = [doc.vocab.strings.add(label) for label in right_labels]
stop_deps = [doc.vocab.strings.add(label) for label in stop_labels]
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token = doc[0]
while token and token.i < len(doclike):
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if token.pos in [PROPN, NOUN, PRON]:
left, right = noun_bounds(
doc, token, np_left_deps, np_right_deps, stop_deps
)
yield left.i, right.i + 1, np_label
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token = right
token = next_token(token)
def is_verb_token(token):
return token.pos in [VERB, AUX]
def next_token(token):
try:
return token.nbor()
except IndexError:
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return None
def noun_bounds(doc, root, np_left_deps, np_right_deps, stop_deps):
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left_bound = root
for token in reversed(list(root.lefts)):
if token.dep in np_left_deps:
left_bound = token
right_bound = root
for token in root.rights:
if token.dep in np_right_deps:
left, right = noun_bounds(
doc, token, np_left_deps, np_right_deps, stop_deps
)
if list(
filter(
lambda t: is_verb_token(t) or t.dep in stop_deps,
doc[left_bound.i : right.i],
)
):
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break
else:
right_bound = right
return left_bound, right_bound
SYNTAX_ITERATORS = {"noun_chunks": noun_chunks}