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Lemmatizer ro (#2319)
* Add Romanian lemmatizer lookup table. Adapted from http://www.lexiconista.com/datasets/lemmatization/ by replacing cedillas with commas (ș and ț). The original dataset is licensed under the Open Database License. * Fix one blatant issue in the Romanian lemmatizer * Romanian examples file * Add ro_tokenizer in conftest * Add Romanian lemmatizer test
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@ -3,6 +3,7 @@ from __future__ import unicode_literals
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from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
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from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
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from .stop_words import STOP_WORDS
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from .stop_words import STOP_WORDS
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from .lemmatizer import LOOKUP
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from ..tokenizer_exceptions import BASE_EXCEPTIONS
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from ..tokenizer_exceptions import BASE_EXCEPTIONS
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from ..norm_exceptions import BASE_NORMS
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from ..norm_exceptions import BASE_NORMS
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@ -17,6 +18,7 @@ class RomanianDefaults(Language.Defaults):
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lex_attr_getters[NORM] = add_lookups(Language.Defaults.lex_attr_getters[NORM], BASE_NORMS)
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lex_attr_getters[NORM] = add_lookups(Language.Defaults.lex_attr_getters[NORM], BASE_NORMS)
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tokenizer_exceptions = update_exc(BASE_EXCEPTIONS, TOKENIZER_EXCEPTIONS)
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tokenizer_exceptions = update_exc(BASE_EXCEPTIONS, TOKENIZER_EXCEPTIONS)
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stop_words = STOP_WORDS
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stop_words = STOP_WORDS
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lemma_lookup = LOOKUP
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class Romanian(Language):
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class Romanian(Language):
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spacy/lang/ro/examples.py
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spacy/lang/ro/examples.py
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# coding: utf8
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from __future__ import unicode_literals
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"""
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Example sentences to test spaCy and its language models.
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>>> from spacy.lang.ro import Romanian
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>>> from spacy.lang.ro.examples import sentences
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>>> nlp = Romanian()
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>>> docs = nlp.pipe(sentences)
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"""
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sentences = [
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"Apple plănuiește să cumpere o companie britanică pentru un miliard de dolari",
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"Municipalitatea din San Francisco ia în calcul interzicerea roboților curieri pe trotuar",
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"Londra este un oraș mare în Regatul Unit",
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"Unde ești?",
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"Cine este președintele Franței?",
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"Care este capitala Statelor Unite?",
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"Când s-a născut Barack Obama?"
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]
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314816
spacy/lang/ro/lemmatizer.py
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314816
spacy/lang/ro/lemmatizer.py
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@ -15,7 +15,7 @@ from .. import util
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# here if it's using spaCy's tokenizer (not a different library)
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# here if it's using spaCy's tokenizer (not a different library)
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# TODO: re-implement generic tokenizer tests
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# TODO: re-implement generic tokenizer tests
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_languages = ['bn', 'da', 'de', 'en', 'es', 'fi', 'fr', 'ga', 'he', 'hu', 'id',
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_languages = ['bn', 'da', 'de', 'en', 'es', 'fi', 'fr', 'ga', 'he', 'hu', 'id',
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'it', 'nb', 'nl', 'pl', 'pt', 'ru', 'sv', 'tr', 'xx']
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'it', 'nb', 'nl', 'pl', 'pt', 'ro', 'ru', 'sv', 'tr', 'xx']
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_models = {'en': ['en_core_web_sm'],
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_models = {'en': ['en_core_web_sm'],
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'de': ['de_core_news_md'],
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'de': ['de_core_news_md'],
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'fr': ['fr_core_news_sm'],
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'fr': ['fr_core_news_sm'],
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@ -100,6 +100,11 @@ def fi_tokenizer():
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return util.get_lang_class('fi').Defaults.create_tokenizer()
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return util.get_lang_class('fi').Defaults.create_tokenizer()
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@pytest.fixture
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def ro_tokenizer():
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return util.get_lang_class('ro').Defaults.create_tokenizer()
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@pytest.fixture
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@pytest.fixture
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def id_tokenizer():
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def id_tokenizer():
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return util.get_lang_class('id').Defaults.create_tokenizer()
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return util.get_lang_class('id').Defaults.create_tokenizer()
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spacy/tests/lang/ro/__init__.py
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spacy/tests/lang/ro/__init__.py
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spacy/tests/lang/ro/test_lemmatizer.py
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spacy/tests/lang/ro/test_lemmatizer.py
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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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@pytest.mark.parametrize('string,lemma', [('câini', 'câine'),
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('expedițiilor', 'expediție'),
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('pensete', 'pensetă'),
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('erau', 'fi')])
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def test_lemmatizer_lookup_assigns(ro_tokenizer, string, lemma):
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tokens = ro_tokenizer(string)
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assert tokens[0].lemma_ == lemma
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