spaCy/spacy/tests/lang/ru/test_lemmatizer.py
Daniël de Kok e2b70df012
Configure isort to use the Black profile, recursively isort the spacy module (#12721)
* Use isort with Black profile

* isort all the things

* Fix import cycles as a result of import sorting

* Add DOCBIN_ALL_ATTRS type definition

* Add isort to requirements

* Remove isort from build dependencies check

* Typo
2023-06-14 17:48:41 +02:00

110 lines
3.9 KiB
Python

import pytest
from spacy.tokens import Doc
pytestmark = pytest.mark.filterwarnings("ignore::DeprecationWarning")
def test_ru_doc_lemmatization(ru_lemmatizer):
words = ["мама", "мыла", "раму"]
pos = ["NOUN", "VERB", "NOUN"]
morphs = [
"Animacy=Anim|Case=Nom|Gender=Fem|Number=Sing",
"Aspect=Imp|Gender=Fem|Mood=Ind|Number=Sing|Tense=Past|VerbForm=Fin|Voice=Act",
"Animacy=Anim|Case=Acc|Gender=Fem|Number=Sing",
]
doc = Doc(ru_lemmatizer.vocab, words=words, pos=pos, morphs=morphs)
doc = ru_lemmatizer(doc)
lemmas = [token.lemma_ for token in doc]
assert lemmas == ["мама", "мыть", "рама"]
@pytest.mark.parametrize(
"text,lemmas",
[
("гвоздики", ["гвоздик", "гвоздика"]),
("люди", ["человек"]),
("реки", ["река"]),
("кольцо", ["кольцо"]),
("пепперони", ["пепперони"]),
],
)
def test_ru_lemmatizer_noun_lemmas(ru_lemmatizer, text, lemmas):
doc = Doc(ru_lemmatizer.vocab, words=[text], pos=["NOUN"])
result_lemmas = ru_lemmatizer.pymorphy2_lemmatize(doc[0])
assert sorted(result_lemmas) == lemmas
@pytest.mark.parametrize(
"text,pos,morph,lemma",
[
("рой", "NOUN", "", "рой"),
("рой", "VERB", "", "рыть"),
("клей", "NOUN", "", "клей"),
("клей", "VERB", "", "клеить"),
("три", "NUM", "", "три"),
("кос", "NOUN", "Number=Sing", "кос"),
("кос", "NOUN", "Number=Plur", "коса"),
("кос", "ADJ", "", "косой"),
("потом", "NOUN", "", "пот"),
("потом", "ADV", "", "потом"),
],
)
def test_ru_lemmatizer_works_with_different_pos_homonyms(
ru_lemmatizer, text, pos, morph, lemma
):
doc = Doc(ru_lemmatizer.vocab, words=[text], pos=[pos], morphs=[morph])
result_lemmas = ru_lemmatizer.pymorphy2_lemmatize(doc[0])
assert result_lemmas == [lemma]
@pytest.mark.parametrize(
"text,morph,lemma",
[
("гвоздики", "Gender=Fem", "гвоздика"),
("гвоздики", "Gender=Masc", "гвоздик"),
("вина", "Gender=Fem", "вина"),
("вина", "Gender=Neut", "вино"),
],
)
def test_ru_lemmatizer_works_with_noun_homonyms(ru_lemmatizer, text, morph, lemma):
doc = Doc(ru_lemmatizer.vocab, words=[text], pos=["NOUN"], morphs=[morph])
result_lemmas = ru_lemmatizer.pymorphy2_lemmatize(doc[0])
assert result_lemmas == [lemma]
def test_ru_lemmatizer_punct(ru_lemmatizer):
doc = Doc(ru_lemmatizer.vocab, words=["«"], pos=["PUNCT"])
assert ru_lemmatizer.pymorphy2_lemmatize(doc[0]) == ['"']
doc = Doc(ru_lemmatizer.vocab, words=["»"], pos=["PUNCT"])
assert ru_lemmatizer.pymorphy2_lemmatize(doc[0]) == ['"']
def test_ru_doc_lookup_lemmatization(ru_lookup_lemmatizer):
assert ru_lookup_lemmatizer.mode == "pymorphy3_lookup"
words = ["мама", "мыла", "раму"]
pos = ["NOUN", "VERB", "NOUN"]
morphs = [
"Animacy=Anim|Case=Nom|Gender=Fem|Number=Sing",
"Aspect=Imp|Gender=Fem|Mood=Ind|Number=Sing|Tense=Past|VerbForm=Fin|Voice=Act",
"Animacy=Anim|Case=Acc|Gender=Fem|Number=Sing",
]
doc = Doc(ru_lookup_lemmatizer.vocab, words=words, pos=pos, morphs=morphs)
doc = ru_lookup_lemmatizer(doc)
lemmas = [token.lemma_ for token in doc]
assert lemmas == ["мама", "мыла", "раму"]
@pytest.mark.parametrize(
"word,lemma",
(
("бременем", "бремя"),
("будешь", "быть"),
("какая-то", "какой-то"),
),
)
def test_ru_lookup_lemmatizer(ru_lookup_lemmatizer, word, lemma):
assert ru_lookup_lemmatizer.mode == "pymorphy3_lookup"
doc = Doc(ru_lookup_lemmatizer.vocab, words=[word])
assert ru_lookup_lemmatizer(doc)[0].lemma_ == lemma