spaCy/spacy/lang/el/syntax_iterators.py

64 lines
2.5 KiB
Python

# coding: utf8
from __future__ import unicode_literals
from ...symbols import NOUN, PROPN, PRON
from ...errors import Errors
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.
if not doc.is_parsed:
raise ValueError(Errors.E029)
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:
flag = False
if word.pos == NOUN:
# check for patterns such as γραμμή παραγωγής
for potential_nmod in word.rights:
if potential_nmod.dep == nmod:
w_range = range(word.left_edge.i, potential_nmod.i + 1)
if any(j in seen for j in w_range):
continue
seen.update(j for j in w_range)
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:
w_range = range(word.left_edge.i, word.i + 1)
if any(j in seen for j in w_range):
continue
seen.update(j for j in w_range)
yield word.left_edge.i, word.i + 1, np_label
SYNTAX_ITERATORS = {"noun_chunks": noun_chunks}