spaCy/spacy/tests/lang/en/test_lemmatizer.py
2017-06-05 02:09:27 +02:00

48 lines
1.5 KiB
Python

# coding: utf-8
from __future__ import unicode_literals
import pytest
@pytest.fixture
def en_lemmatizer(EN):
return EN.Defaults.create_lemmatizer()
@pytest.mark.models('en')
@pytest.mark.parametrize('text,lemmas', [("aardwolves", ["aardwolf"]),
("aardwolf", ["aardwolf"]),
("planets", ["planet"]),
("ring", ["ring"]),
("axes", ["axis", "axe", "ax"])])
def test_en_lemmatizer_noun_lemmas(en_lemmatizer, text, lemmas):
assert en_lemmatizer.noun(text) == set(lemmas)
@pytest.mark.xfail
@pytest.mark.models('en')
def test_en_lemmatizer_base_forms(en_lemmatizer):
assert en_lemmatizer.noun('dive', {'number': 'sing'}) == set(['dive'])
assert en_lemmatizer.noun('dive', {'number': 'plur'}) == set(['diva'])
@pytest.mark.models('en')
def test_en_lemmatizer_base_form_verb(en_lemmatizer):
assert en_lemmatizer.verb('saw', {'verbform': 'past'}) == set(['see'])
@pytest.mark.models('en')
def test_en_lemmatizer_punct(en_lemmatizer):
assert en_lemmatizer.punct('') == set(['"'])
assert en_lemmatizer.punct('') == set(['"'])
@pytest.mark.models('en')
def test_en_lemmatizer_lemma_assignment(EN):
text = "Bananas in pyjamas are geese."
doc = EN.make_doc(text)
EN.tensorizer(doc)
assert all(t.lemma_ == '' for t in doc)
EN.tagger(doc)
assert all(t.lemma_ != '' for t in doc)