mirror of https://github.com/explosion/spaCy.git
59 lines
2.4 KiB
Python
59 lines
2.4 KiB
Python
# coding: utf8
|
|
from __future__ import unicode_literals
|
|
|
|
from ...symbols import NOUN, PROPN, PRON
|
|
|
|
|
|
def noun_chunks(obj):
|
|
"""
|
|
Detect base noun phrases. Works on both Doc and Span.
|
|
"""
|
|
# It follows the logic of the noun chunks finder of English language,
|
|
# adjusted to some Greek language special characteristics.
|
|
# obj tag corrects some DEP tagger mistakes.
|
|
# Further improvement of the models will eliminate the need for this tag.
|
|
labels = ["nsubj", "obj", "iobj", "appos", "ROOT", "obl"]
|
|
doc = obj.doc # Ensure works on both Doc and Span.
|
|
np_deps = [doc.vocab.strings.add(label) for label in labels]
|
|
conj = doc.vocab.strings.add("conj")
|
|
nmod = doc.vocab.strings.add("nmod")
|
|
np_label = doc.vocab.strings.add("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
|
|
flag = False
|
|
if word.pos == NOUN:
|
|
# check for patterns such as γραμμή παραγωγής
|
|
for potential_nmod in word.rights:
|
|
if potential_nmod.dep == nmod:
|
|
seen.update(
|
|
j for j in range(word.left_edge.i, potential_nmod.i + 1)
|
|
)
|
|
yield word.left_edge.i, potential_nmod.i + 1, np_label
|
|
flag = True
|
|
break
|
|
if flag is False:
|
|
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:
|
|
# covers the case: έχει όμορφα και έξυπνα παιδιά
|
|
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
|
|
|
|
|
|
SYNTAX_ITERATORS = {"noun_chunks": noun_chunks}
|