mirror of
https://github.com/explosion/spaCy.git
synced 2024-12-27 10:26:35 +03:00
43 lines
1.1 KiB
Python
43 lines
1.1 KiB
Python
from __future__ import unicode_literals
|
|
import spacy
|
|
from spacy.vocab import Vocab
|
|
from spacy.matcher import Matcher
|
|
from spacy.tokens.doc import Doc
|
|
from spacy.attrs import *
|
|
from spacy.pipeline import EntityRecognizer
|
|
|
|
import pytest
|
|
|
|
|
|
@pytest.fixture(scope="module")
|
|
def en_vocab():
|
|
return spacy.get_lang_class('en').Defaults.create_vocab()
|
|
|
|
|
|
@pytest.fixture(scope="module")
|
|
def entity_recognizer(en_vocab):
|
|
return EntityRecognizer(en_vocab, features=[(2,), (3,)])
|
|
|
|
@pytest.fixture
|
|
def animal(en_vocab):
|
|
return nlp.vocab.strings[u"ANIMAL"]
|
|
|
|
|
|
@pytest.fixture
|
|
def doc(en_vocab, entity_recognizer):
|
|
doc = Doc(en_vocab, words=[u"this", u"is", u"a", u"lion"])
|
|
entity_recognizer(doc)
|
|
return doc
|
|
|
|
|
|
def test_set_ents_iob(doc):
|
|
assert len(list(doc.ents)) == 0
|
|
tags = [w.ent_iob_ for w in doc]
|
|
assert tags == (['O'] * len(doc))
|
|
doc.ents = [(doc.vocab.strings['ANIMAL'], 3, 4)]
|
|
tags = [w.ent_iob_ for w in doc]
|
|
assert tags == ['O', 'O', 'O', 'B']
|
|
doc.ents = [(doc.vocab.strings['WORD'], 0, 2)]
|
|
tags = [w.ent_iob_ for w in doc]
|
|
assert tags == ['B', 'I', 'O', 'O']
|