mirror of
https://github.com/explosion/spaCy.git
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72 lines
3.4 KiB
Python
72 lines
3.4 KiB
Python
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# coding: utf-8
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from __future__ import unicode_literals
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import pytest
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from ....tokens.doc import Doc
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@pytest.fixture
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def ru_lemmatizer(RU):
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return RU.Defaults.create_lemmatizer()
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# @pytest.mark.models('ru')
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# def test_doc_lemmatization(RU):
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# doc = Doc(RU.vocab, words=['мама', 'мыла', 'раму'])
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# doc[0].tag_ = 'NOUN__Animacy=Anim|Case=Nom|Gender=Fem|Number=Sing'
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# doc[1].tag_ = 'VERB__Aspect=Imp|Gender=Fem|Mood=Ind|Number=Sing|Tense=Past|VerbForm=Fin|Voice=Act'
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# doc[2].tag_ = 'NOUN__Animacy=Anim|Case=Acc|Gender=Fem|Number=Sing'
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#
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# lemmas = [token.lemma_ for token in doc]
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# assert lemmas == ['мама', 'мыть', 'рама']
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@pytest.mark.models('ru')
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@pytest.mark.parametrize('text,lemmas', [('гвоздики', ['гвоздик', 'гвоздика']),
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('люди', ['человек']),
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('реки', ['река']),
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('кольцо', ['кольцо']),
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('пепперони', ['пепперони'])])
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def test_ru_lemmatizer_noun_lemmas(ru_lemmatizer, text, lemmas):
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assert sorted(ru_lemmatizer.noun(text)) == lemmas
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@pytest.mark.models('ru')
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@pytest.mark.parametrize('text,pos,morphology,lemma', [('рой', 'NOUN', None, 'рой'),
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('рой', 'VERB', None, 'рыть'),
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('клей', 'NOUN', None, 'клей'),
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('клей', 'VERB', None, 'клеить'),
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('три', 'NUM', None, 'три'),
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('кос', 'NOUN', {'Number': 'Sing'}, 'кос'),
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('кос', 'NOUN', {'Number': 'Plur'}, 'коса'),
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('кос', 'ADJ', None, 'косой'),
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('потом', 'NOUN', None, 'пот'),
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('потом', 'ADV', None, 'потом')
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])
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def test_ru_lemmatizer_works_with_different_pos_homonyms(ru_lemmatizer, text, pos, morphology, lemma):
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assert ru_lemmatizer(text, pos, morphology) == [lemma]
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@pytest.mark.models('ru')
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@pytest.mark.parametrize('text,morphology,lemma', [('гвоздики', {'Gender': 'Fem'}, 'гвоздика'),
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('гвоздики', {'Gender': 'Masc'}, 'гвоздик'),
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('вина', {'Gender': 'Fem'}, 'вина'),
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('вина', {'Gender': 'Neut'}, 'вино')
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])
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def test_ru_lemmatizer_works_with_noun_homonyms(ru_lemmatizer, text, morphology, lemma):
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assert ru_lemmatizer.noun(text, morphology) == [lemma]
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# @pytest.mark.models('ru')
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# def test_ru_lemmatizer_punct(ru_lemmatizer):
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# assert ru_lemmatizer.punct('“') == ['"']
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# assert ru_lemmatizer.punct('“') == ['"']
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#
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#
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# @pytest.mark.models('ru')
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# def test_ru_lemmatizer_lemma_assignment(RU):
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# text = "А роза упала на лапу Азора."
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# doc = RU.make_doc(text)
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# RU.tagger(doc)
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# assert all(t.lemma_ != '' for t in doc)
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