mirror of
https://github.com/explosion/spaCy.git
synced 2025-10-31 16:07:41 +03:00
Updated Russian Language, added lemmatizer, norm exceptions and lex
attrs
This commit is contained in:
Vadim Mazaev
parent
a0739a06d4
commit
52ee1f9bf9
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@ -1,64 +1,36 @@
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# encoding: utf8
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from __future__ import unicode_literals, print_function
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from ..language import Language
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from ..attrs import LANG
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from ..tokens import Doc
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from .language_data import *
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from .stop_words import STOP_WORDS
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from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
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from .norm_exceptions import NORM_EXCEPTIONS
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from .lex_attrs import LEX_ATTRS
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from .lemmatizer import RussianLemmatizer
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class RussianTokenizer(object):
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_morph = None
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def __init__(self, spacy_tokenizer, cls, nlp=None):
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try:
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from pymorphy2 import MorphAnalyzer
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except ImportError:
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raise ImportError(
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"The Russian tokenizer requires the pymorphy2 library: "
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"try to fix it with "
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"pip install pymorphy2==0.8")
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RussianTokenizer._morph = RussianTokenizer._create_morph(MorphAnalyzer)
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self.vocab = nlp.vocab if nlp else cls.create_vocab(nlp)
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self._spacy_tokenizer = spacy_tokenizer
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def __call__(self, text):
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words = [self._normalize(RussianTokenizer._get_word(token))
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for token in self._spacy_tokenizer(text)]
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return Doc(self.vocab, words, [False] * len(words))
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@staticmethod
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def _get_word(token):
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return token.lemma_ if len(token.lemma_) > 0 else token.text
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@classmethod
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def _normalize(cls, word):
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return cls._morph.parse(word)[0].normal_form
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@classmethod
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def _create_morph(cls, morph_analyzer_class):
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if not cls._morph:
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cls._morph = morph_analyzer_class()
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return cls._morph
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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 ...util import update_exc, add_lookups
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from ...language import Language
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from ...attrs import LANG, LIKE_NUM, NORM
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class RussianDefaults(Language.Defaults):
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lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
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lex_attr_getters.update(LEX_ATTRS)
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lex_attr_getters[LANG] = lambda text: 'ru'
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tokenizer_exceptions = TOKENIZER_EXCEPTIONS
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lex_attr_getters[NORM] = add_lookups(Language.Defaults.lex_attr_getters[NORM],
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BASE_NORMS, NORM_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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@classmethod
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def create_tokenizer(cls, nlp=None):
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tokenizer = super(RussianDefaults, cls).create_tokenizer(nlp)
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return RussianTokenizer(tokenizer, cls, nlp)
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def create_lemmatizer(cls, nlp=None):
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return RussianLemmatizer()
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class Russian(Language):
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lang = 'ru'
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Defaults = RussianDefaults
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__all__ = ['Russian']
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@ -1,18 +0,0 @@
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# encoding: utf8
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from __future__ import unicode_literals
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from .. import language_data as base
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from ..language_data import update_exc, strings_to_exc
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from .stop_words import STOP_WORDS
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from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
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STOP_WORDS = set(STOP_WORDS)
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TOKENIZER_EXCEPTIONS = dict(TOKENIZER_EXCEPTIONS)
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update_exc(TOKENIZER_EXCEPTIONS, strings_to_exc(base.EMOTICONS))
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__all__ = ["STOP_WORDS", "TOKENIZER_EXCEPTIONS"]
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232
spacy/lang/ru/lemmatizer.py
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232
spacy/lang/ru/lemmatizer.py
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@ -0,0 +1,232 @@
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# coding: utf8
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from ...symbols import (
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ADJ, DET, NOUN, NUM, PRON, PROPN, VERB
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)
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from ...lemmatizer import Lemmatizer
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class RussianLemmatizer(Lemmatizer):
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_morph = None
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def __init__(self):
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super().__init__()
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try:
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from pymorphy2 import MorphAnalyzer
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except ImportError:
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raise ImportError(
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'The Russian lemmatizer requires the pymorphy2 library: '
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'try to fix it with "pip install pymorphy2"')
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if RussianLemmatizer._morph is None:
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RussianLemmatizer._morph = MorphAnalyzer()
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def __call__(self, string, univ_pos, morphology=None):
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univ_pos = self.normalize_univ_pos(univ_pos)
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if univ_pos not in ('ADJ', 'DET', 'NOUN', 'NUM', 'PRON', 'PROPN', 'VERB'):
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# Skip unchangeable pos
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return [string.lower()]
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analyses = self._morph.parse(string)
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filtered_analyses = []
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for analysis in analyses:
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if not analysis.is_known:
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# Skip suggested parse variant for unknown word for pymorphy
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continue
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analysis_pos, _ = oc2ud(str(analysis.tag))
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if analysis_pos == univ_pos \
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or (analysis_pos in ('NOUN', 'PROPN') and univ_pos in ('NOUN', 'PROPN')):
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filtered_analyses.append(analysis)
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if not len(filtered_analyses):
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return [string.lower()]
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if morphology is None:
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return list(set([analysis.normal_form for analysis in filtered_analyses]))
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if univ_pos in ('ADJ', 'DET', 'NOUN', 'PROPN'):
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features_to_compare = ['Case', 'Number', 'Gender']
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elif univ_pos == 'NUM':
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features_to_compare = ['Case', 'Gender']
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elif univ_pos == 'PRON':
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features_to_compare = ['Case', 'Number', 'Gender', 'Person']
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else: # VERB
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features_to_compare = ['Aspect', 'Gender', 'Mood', 'Number', 'Tense', 'VerbForm', 'Voice']
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analyses, filtered_analyses = filtered_analyses, []
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for analysis in analyses:
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_, analysis_morph = oc2ud(str(analysis.tag))
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for feature in features_to_compare:
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if feature in morphology and morphology[feature] != analysis_morph[feature]:
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break
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else:
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filtered_analyses.append(analysis)
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if not len(filtered_analyses):
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return [string.lower()]
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return list(set([analysis.normal_form for analysis in filtered_analyses]))
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@staticmethod
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def normalize_univ_pos(univ_pos):
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if isinstance(univ_pos, str):
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return univ_pos.upper()
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symbols_to_str = {
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ADJ: 'ADJ',
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DET: 'DET',
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NOUN: 'NOUN',
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NUM: 'NUM',
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PRON: 'PRON',
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PROPN: 'PROPN',
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VERB: 'VERB'
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}
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if univ_pos in symbols_to_str:
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return symbols_to_str[univ_pos]
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return None
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def is_base_form(self, univ_pos, morphology=None):
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# TODO
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raise NotImplementedError
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# ('ADJ', 'DET', 'NOUN', 'NUM', 'PRON', 'PROPN', 'VERB'):
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def det(self, string, morphology=None):
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return self(string, 'det', morphology)
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def num(self, string, morphology=None):
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return self(string, 'num', morphology)
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def pron(self, string, morphology=None):
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return self(string, 'pron', morphology)
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def lookup(self, string):
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analyses = self._morph.parse(string)
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if len(analyses) == 1:
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return analyses[0].normal_form
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return string
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def oc2ud(oc_tag):
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gram_map = {
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'_POS': {
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'ADJF': 'ADJ',
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'ADJS': 'ADJ',
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'ADVB': 'ADV',
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'Apro': 'DET',
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'COMP': 'ADJ', # Can also be an ADV - unchangeable
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'CONJ': 'CCONJ', # Can also be a SCONJ - both unchangeable ones
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'GRND': 'VERB',
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'INFN': 'VERB',
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'INTJ': 'INTJ',
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'NOUN': 'NOUN',
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'NPRO': 'PRON',
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'NUMR': 'NUM',
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'NUMB': 'NUM',
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'PNCT': 'PUNCT',
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'PRCL': 'PART',
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'PREP': 'ADP',
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'PRTF': 'VERB',
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'PRTS': 'VERB',
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'VERB': 'VERB',
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},
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'Animacy': {
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'anim': 'Anim',
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'inan': 'Inan',
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},
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'Aspect': {
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'impf': 'Imp',
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'perf': 'Perf',
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},
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'Case': {
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'ablt': 'Ins',
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'accs': 'Acc',
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'datv': 'Dat',
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'gen1': 'Gen',
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'gen2': 'Gen',
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'gent': 'Gen',
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'loc2': 'Loc',
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'loct': 'Loc',
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'nomn': 'Nom',
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'voct': 'Voc',
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},
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'Degree': {
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'COMP': 'Cmp',
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'Supr': 'Sup',
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},
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'Gender': {
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'femn': 'Fem',
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'masc': 'Masc',
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'neut': 'Neut',
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},
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'Mood': {
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'impr': 'Imp',
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'indc': 'Ind',
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},
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'Number': {
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'plur': 'Plur',
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'sing': 'Sing',
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},
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'NumForm': {
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'NUMB': 'Digit',
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},
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'Person': {
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'1per': '1',
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'2per': '2',
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'3per': '3',
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'excl': '2',
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'incl': '1',
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},
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'Tense': {
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'futr': 'Fut',
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'past': 'Past',
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'pres': 'Pres',
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},
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'Variant': {
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'ADJS': 'Brev',
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'PRTS': 'Brev',
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},
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'VerbForm': {
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'GRND': 'Conv',
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'INFN': 'Inf',
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'PRTF': 'Part',
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'PRTS': 'Part',
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'VERB': 'Fin',
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},
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'Voice': {
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'actv': 'Act',
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'pssv': 'Pass',
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},
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'Abbr': {
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'Abbr': 'Yes'
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}
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}
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pos = 'X'
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morphology = dict()
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unmatched = set()
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grams = oc_tag.replace(' ', ',').split(',')
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for gram in grams:
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match = False
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for categ, gmap in sorted(gram_map.items()):
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if gram in gmap:
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match = True
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if categ == '_POS':
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pos = gmap[gram]
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else:
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morphology[categ] = gmap[gram]
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if not match:
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unmatched.add(gram)
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while len(unmatched) > 0:
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gram = unmatched.pop()
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if gram in ('Name', 'Patr', 'Surn', 'Geox', 'Orgn'):
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pos = 'PROPN'
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elif gram == 'Auxt':
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pos = 'AUX'
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elif gram == 'Pltm':
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morphology['Number'] = 'Ptan'
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return pos, morphology
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if __name__ == '__main__':
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l = RussianLemmatizer()
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print(l.noun('гвоздики', {'Gender': 'Fem'}))
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35
spacy/lang/ru/lex_attrs.py
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35
spacy/lang/ru/lex_attrs.py
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@ -0,0 +1,35 @@
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# coding: utf8
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from __future__ import unicode_literals
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from ...attrs import LIKE_NUM
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_num_words = [
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'ноль', 'один', 'два', 'три', 'четыре', 'пять', 'шесть', 'семь', 'восемь', 'девять',
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'десять', 'одиннадцать', 'двенадцать', 'тринадцать', 'четырнадцать',
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'пятнадцать', 'шестнадцать', 'семнадцать', 'восемнадцать', 'девятнадцать',
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'двадцать', 'тридцать', 'сорок', 'пятдесят', 'шестдесят', 'семдесят', 'восемдесят', 'девяносто',
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'сто', 'двести', 'триста', 'четыреста', 'пятсот', 'шестсот', 'семсот', 'восемсот', 'девятсот',
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'тысяча', 'миллион', 'миллиад', 'триллион', 'квадриллион', 'квинтиллион']
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def like_num(text):
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text = text.replace(',', '').replace('.', '')
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if text.isdigit():
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return True
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if text.count('/') == 1:
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num, denom = text.split('/')
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if num.isdigit() and denom.isdigit():
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return True
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if text in _num_words:
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return True
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return False
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LEX_ATTRS = {
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LIKE_NUM: like_num
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}
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34
spacy/lang/ru/norm_exceptions.py
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34
spacy/lang/ru/norm_exceptions.py
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@ -0,0 +1,34 @@
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# coding: utf8
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from __future__ import unicode_literals
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_exc = {
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# Slang
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'прив': 'привет',
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# Weekdays abbreviations
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"пн.": "понедельник",
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"вт.": "вторник",
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"ср.": "среда",
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"чт.": "четверг",
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"пт.": "пятница",
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"сб.": "суббота",
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"вс.": "воскресенье",
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# Months abbreviations
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"янв.": "январь",
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"фев.": "февраль",
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"мар.": "март",
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"апр.": "апрель",
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}
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NORM_EXCEPTIONS = {}
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for string, norm in _exc.items():
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NORM_EXCEPTIONS[string] = norm
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NORM_EXCEPTIONS[string.title()] = norm
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if string.endswith('.'):
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NORM_EXCEPTIONS[string[:-1]] = norm
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NORM_EXCEPTIONS[string.title()[:-1]] = norm
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@ -1,29 +1,9 @@
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# encoding: utf8
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from __future__ import unicode_literals
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from ..symbols import *
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from ...symbols import ORTH, LEMMA
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TOKENIZER_EXCEPTIONS = {
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"Пн.": [
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{ORTH: "Пн.", LEMMA: "Понедельник"}
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],
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"Вт.": [
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{ORTH: "Вт.", LEMMA: "Вторник"}
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],
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"Ср.": [
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{ORTH: "Ср.", LEMMA: "Среда"}
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],
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"Чт.": [
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{ORTH: "Чт.", LEMMA: "Четверг"}
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],
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"Пт.": [
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{ORTH: "Пт.", LEMMA: "Пятница"}
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],
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"Сб.": [
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{ORTH: "Сб.", LEMMA: "Суббота"}
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],
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"Вс.": [
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{ORTH: "Вс.", LEMMA: "Воскресенье"}
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],
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}
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}
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