mirror of https://github.com/explosion/spaCy.git
32 lines
813 B
Python
32 lines
813 B
Python
# coding: utf-8
|
|
from __future__ import unicode_literals
|
|
|
|
import spacy
|
|
from spacy.attrs import ORTH
|
|
|
|
import pytest
|
|
|
|
|
|
@pytest.mark.models
|
|
def test_issue429():
|
|
|
|
nlp = spacy.load('en', parser=False)
|
|
|
|
|
|
def merge_phrases(matcher, doc, i, matches):
|
|
if i != len(matches) - 1:
|
|
return None
|
|
spans = [(ent_id, label, doc[start:end]) for ent_id, label, start, end in matches]
|
|
for ent_id, label, span in spans:
|
|
span.merge('NNP' if label else span.root.tag_, span.text, nlp.vocab.strings[label])
|
|
|
|
doc = nlp('a')
|
|
nlp.matcher.add('key', label='TEST', attrs={}, specs=[[{ORTH: 'a'}]], on_match=merge_phrases)
|
|
doc = nlp.tokenizer('a b c')
|
|
nlp.tagger(doc)
|
|
nlp.matcher(doc)
|
|
|
|
for word in doc:
|
|
print(word.text, word.ent_iob_, word.ent_type_)
|
|
nlp.entity(doc)
|