mirror of
https://github.com/explosion/spaCy.git
synced 2024-11-11 04:08:09 +03:00
70 lines
2.7 KiB
Cython
70 lines
2.7 KiB
Cython
# coding: utf-8
|
|
from __future__ import unicode_literals
|
|
|
|
from ..parts_of_speech cimport NOUN, PROPN, PRON
|
|
|
|
|
|
def english_noun_chunks(obj):
|
|
"""
|
|
Detect base noun phrases from a dependency parse.
|
|
Works on both Doc and Span.
|
|
"""
|
|
labels = ['nsubj', 'dobj', 'nsubjpass', 'pcomp', 'pobj',
|
|
'attr', 'ROOT']
|
|
doc = obj.doc # Ensure works on both Doc and Span.
|
|
np_deps = [doc.vocab.strings[label] for label in labels]
|
|
conj = doc.vocab.strings['conj']
|
|
np_label = doc.vocab.strings['NP']
|
|
seen = set()
|
|
for i, word in enumerate(obj):
|
|
if word.pos not in (NOUN, PROPN, PRON):
|
|
continue
|
|
# Prevent nested chunks from being produced
|
|
if word.i in seen:
|
|
continue
|
|
if word.dep in np_deps:
|
|
if any(w.i in seen for w in word.subtree):
|
|
continue
|
|
seen.update(j for j in range(word.left_edge.i, word.i+1))
|
|
yield word.left_edge.i, word.i+1, np_label
|
|
elif word.dep == conj:
|
|
head = word.head
|
|
while head.dep == conj and head.head.i < head.i:
|
|
head = head.head
|
|
# If the head is an NP, and we're coordinated to it, we're an NP
|
|
if head.dep in np_deps:
|
|
if any(w.i in seen for w in word.subtree):
|
|
continue
|
|
seen.update(j for j in range(word.left_edge.i, word.i+1))
|
|
yield word.left_edge.i, word.i+1, np_label
|
|
|
|
|
|
# this iterator extracts spans headed by NOUNs starting from the left-most
|
|
# syntactic dependent until the NOUN itself
|
|
# for close apposition and measurement construction, the span is sometimes
|
|
# extended to the right of the NOUN
|
|
# example: "eine Tasse Tee" (a cup (of) tea) returns "eine Tasse Tee" and not
|
|
# just "eine Tasse", same for "das Thema Familie"
|
|
def german_noun_chunks(obj):
|
|
labels = ['sb', 'oa', 'da', 'nk', 'mo', 'ag', 'ROOT', 'root', 'cj', 'pd', 'og', 'app']
|
|
doc = obj.doc # Ensure works on both Doc and Span.
|
|
np_label = doc.vocab.strings['NP']
|
|
np_deps = set(doc.vocab.strings[label] for label in labels)
|
|
close_app = doc.vocab.strings['nk']
|
|
|
|
rbracket = 0
|
|
for i, word in enumerate(obj):
|
|
if i < rbracket:
|
|
continue
|
|
if word.pos in (NOUN, PROPN, PRON) and word.dep in np_deps:
|
|
rbracket = word.i+1
|
|
# try to extend the span to the right
|
|
# to capture close apposition/measurement constructions
|
|
for rdep in doc[word.i].rights:
|
|
if rdep.pos in (NOUN, PROPN) and rdep.dep == close_app:
|
|
rbracket = rdep.i+1
|
|
yield word.left_edge.i, rbracket, np_label
|
|
|
|
|
|
CHUNKERS = {'en': english_noun_chunks, 'de': german_noun_chunks}
|