feat(spanish model): add the spanish noun chunker
# coding: utf-8
from __future__ import unicode_literals
-from ..parts_of_speech cimport NOUN, PROPN, PRON
+from ..parts_of_speech cimport NOUN, PROPN, PRON, VERB, AUX
def english_noun_chunks(obj):
@@ -66,4 +66,55 @@ def german_noun_chunks(obj):
yield word.left_edge.i, rbracket, np_label
-CHUNKERS = {'en': english_noun_chunks, 'de': german_noun_chunks}
+def es_noun_chunks(obj):
+
+ doc = obj.doc
+ np_label = doc.vocab.strings['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[label] for label in left_labels]
+ np_right_deps = [doc.vocab.strings[label] for label in right_labels]
+ stop_deps = [doc.vocab.strings[label] for label in stop_labels]
+
+ def next_token(token):
+ try:
+ return token.nbor()
+ except:
+ return None
+
+ def noun_bounds(root):
+
+ def is_verb_token(token):
+ return token.pos in [VERB, AUX]
+
+ 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(token)
+
+ if list(filter(lambda t: is_verb_token(t) or t.dep in stop_deps, doc[left_bound.i: right.i])):
+ break
+ else:
+ right_bound = right
+
+ return left_bound, right_bound
+
+
+ token = doc[0]
+ while token and token.i < len(doc):
+ if token.pos in [PROPN, NOUN, PRON]:
+ left, right = noun_bounds(token)
+ yield left.i, right.i+1, np_label
+ token = right
+ token = next_token(token)
+
+
+CHUNKERS = {'en': english_noun_chunks, 'de': german_noun_chunks, 'es': es_noun_chunks}
