mirror of
https://github.com/explosion/spaCy.git
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120 lines
3.7 KiB
Python
120 lines
3.7 KiB
Python
# 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, Token
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from ...tokenizer import Tokenizer
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from .tag_map import TAG_MAP
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import re
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from collections import namedtuple
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ShortUnitWord = namedtuple('ShortUnitWord', ['surface', 'lemma', 'pos'])
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# XXX Is this the right place for this?
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Token.set_extension('mecab_tag', default=None)
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def try_mecab_import():
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"""Mecab is required for Japanese support, so check for it.
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It it's not available blow up and explain how to fix it."""
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try:
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import MeCab
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return MeCab
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except ImportError:
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raise ImportError("Japanese support requires MeCab: "
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"https://github.com/SamuraiT/mecab-python3")
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def resolve_pos(token):
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"""If necessary, add a field to the POS tag for UD mapping.
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Under Universal Dependencies, sometimes the same Unidic POS tag can
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be mapped differently depending on the literal token or its context
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in the sentence. This function adds information to the POS tag to
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resolve ambiguous mappings.
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"""
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# NOTE: This is a first take. The rules here are crude approximations.
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# For many of these, full dependencies are needed to properly resolve
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# PoS mappings.
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if token.pos == '連体詞,*,*,*':
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if re.match('^[こそあど此其彼]の', token.surface):
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return token.pos + ',DET'
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if re.match('^[こそあど此其彼]', token.surface):
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return token.pos + ',PRON'
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else:
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return token.pos + ',ADJ'
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return token.pos
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def detailed_tokens(tokenizer, text):
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"""Format Mecab output into a nice data structure, based on Janome."""
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node = tokenizer.parseToNode(text)
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node = node.next # first node is beginning of sentence and empty, skip it
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words = []
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while node.posid != 0:
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surface = node.surface
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base = surface # a default value. Updated if available later.
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parts = node.feature.split(',')
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pos = ','.join(parts[0:4])
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if len(parts) > 7:
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# this information is only available for words in the tokenizer dictionary
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base = parts[7]
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words.append( ShortUnitWord(surface, base, pos) )
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node = node.next
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return words
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class JapaneseTokenizer(object):
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def __init__(self, cls, nlp=None):
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self.vocab = nlp.vocab if nlp is not None else cls.create_vocab(nlp)
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MeCab = try_mecab_import()
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self.tokenizer = MeCab.Tagger()
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def __call__(self, text):
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dtokens = detailed_tokens(self.tokenizer, text)
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words = [x.surface for x in dtokens]
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doc = Doc(self.vocab, words=words, spaces=[False]*len(words))
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for token, dtoken in zip(doc, dtokens):
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token._.mecab_tag = dtoken.pos
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token.tag_ = resolve_pos(dtoken)
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token.lemma_ = dtoken.lemma
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return doc
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# add dummy methods for to_bytes, from_bytes, to_disk and from_disk to
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# allow serialization (see #1557)
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def to_bytes(self, **exclude):
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return b''
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def from_bytes(self, bytes_data, **exclude):
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return self
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def to_disk(self, path, **exclude):
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return None
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def from_disk(self, path, **exclude):
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return self
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class JapaneseDefaults(Language.Defaults):
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lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
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lex_attr_getters[LANG] = lambda text: 'ja'
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tag_map = TAG_MAP
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@classmethod
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def create_tokenizer(cls, nlp=None):
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return JapaneseTokenizer(cls, nlp)
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class Japanese(Language):
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lang = 'ja'
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Defaults = JapaneseDefaults
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Tokenizer = JapaneseTokenizer
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def make_doc(self, text):
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return self.tokenizer(text)
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__all__ = ['Japanese']
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