# encoding: utf8 from __future__ import unicode_literals, print_function import re from collections import namedtuple from .tag_map import TAG_MAP from ...attrs import LANG from ...language import Language from ...tokens import Doc, Token from ...util import DummyTokenizer ShortUnitWord = namedtuple("ShortUnitWord", ["surface", "lemma", "pos"]) # TODO: Is this the right place for this? Token.set_extension("mecab_tag", default=None) def try_mecab_import(): """Mecab is required for Japanese support, so check for it. It it's not available blow up and explain how to fix it.""" try: import MeCab return MeCab except ImportError: raise ImportError( "Japanese support requires MeCab: " "https://github.com/SamuraiT/mecab-python3" ) def resolve_pos(token): """If necessary, add a field to the POS tag for UD mapping. Under Universal Dependencies, sometimes the same Unidic POS tag can be mapped differently depending on the literal token or its context in the sentence. This function adds information to the POS tag to resolve ambiguous mappings. """ # TODO: This is a first take. The rules here are crude approximations. # For many of these, full dependencies are needed to properly resolve # PoS mappings. if token.pos == "連体詞,*,*,*": if re.match(r"[こそあど此其彼]の", token.surface): return token.pos + ",DET" if re.match(r"[こそあど此其彼]", token.surface): return token.pos + ",PRON" return token.pos + ",ADJ" return token.pos def detailed_tokens(tokenizer, text): """Format Mecab output into a nice data structure, based on Janome.""" node = tokenizer.parseToNode(text) node = node.next # first node is beginning of sentence and empty, skip it words = [] while node.posid != 0: surface = node.surface base = surface # a default value. Updated if available later. parts = node.feature.split(",") pos = ",".join(parts[0:4]) if len(parts) > 7: # this information is only available for words in the tokenizer # dictionary base = parts[7] words.append(ShortUnitWord(surface, base, pos)) node = node.next return words class JapaneseTokenizer(DummyTokenizer): def __init__(self, cls, nlp=None): self.vocab = nlp.vocab if nlp is not None else cls.create_vocab(nlp) self.tokenizer = try_mecab_import().Tagger() self.tokenizer.parseToNode("") # see #2901 def __call__(self, text): dtokens = detailed_tokens(self.tokenizer, text) words = [x.surface for x in dtokens] spaces = [False] * len(words) doc = Doc(self.vocab, words=words, spaces=spaces) for token, dtoken in zip(doc, dtokens): token._.mecab_tag = dtoken.pos token.tag_ = resolve_pos(dtoken) token.lemma_ = dtoken.lemma return doc class JapaneseDefaults(Language.Defaults): lex_attr_getters = dict(Language.Defaults.lex_attr_getters) lex_attr_getters[LANG] = lambda _text: "ja" tag_map = TAG_MAP @classmethod def create_tokenizer(cls, nlp=None): return JapaneseTokenizer(cls, nlp) class Japanese(Language): lang = "ja" Defaults = JapaneseDefaults def make_doc(self, text): return self.tokenizer(text) __all__ = ["Japanese"]