mirror of
https://github.com/explosion/spaCy.git
synced 2024-11-11 04:08:09 +03:00
f95ecedd83
* test sPacy commit to git fri 04052019 10:54 * change Data format from my format to master format * ทัทั้งนี้ ---> ทั้งนี้ * delete stop_word translate from Eng * Adjust formatting and readability * add Thai norm_exception * Add Dobita21 SCA * editรึ : หรือ, * Update Dobita21.md * Auto-format * Integrate norms into language defaults * add acronym and some norm exception words * add lex_attrs * Add lexical attribute getters into the language defaults * fix LEX_ATTRS Co-authored-by: Donut <dobita21@gmail.com> Co-authored-by: Ines Montani <ines@ines.io>
61 lines
1.7 KiB
Python
61 lines
1.7 KiB
Python
# coding: utf8
|
|
from __future__ import unicode_literals
|
|
|
|
from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
|
|
from .tag_map import TAG_MAP
|
|
from .stop_words import STOP_WORDS
|
|
from .norm_exceptions import NORM_EXCEPTIONS
|
|
from .lex_attrs import LEX_ATTRS
|
|
|
|
from ..norm_exceptions import BASE_NORMS
|
|
from ...attrs import LANG, NORM
|
|
from ...language import Language
|
|
from ...tokens import Doc
|
|
from ...util import DummyTokenizer, add_lookups
|
|
|
|
|
|
class ThaiTokenizer(DummyTokenizer):
|
|
def __init__(self, cls, nlp=None):
|
|
try:
|
|
from pythainlp.tokenize import word_tokenize
|
|
except ImportError:
|
|
raise ImportError(
|
|
"The Thai tokenizer requires the PyThaiNLP library: "
|
|
"https://github.com/PyThaiNLP/pythainlp"
|
|
)
|
|
|
|
self.word_tokenize = word_tokenize
|
|
self.vocab = nlp.vocab if nlp is not None else cls.create_vocab(nlp)
|
|
|
|
def __call__(self, text):
|
|
words = list(self.word_tokenize(text, "newmm"))
|
|
spaces = [False] * len(words)
|
|
return Doc(self.vocab, words=words, spaces=spaces)
|
|
|
|
|
|
class ThaiDefaults(Language.Defaults):
|
|
lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
|
|
lex_attr_getters.update(LEX_ATTRS)
|
|
lex_attr_getters[LANG] = lambda _text: "th"
|
|
lex_attr_getters[NORM] = add_lookups(
|
|
Language.Defaults.lex_attr_getters[NORM], BASE_NORMS, NORM_EXCEPTIONS
|
|
)
|
|
tokenizer_exceptions = dict(TOKENIZER_EXCEPTIONS)
|
|
tag_map = TAG_MAP
|
|
stop_words = STOP_WORDS
|
|
|
|
@classmethod
|
|
def create_tokenizer(cls, nlp=None):
|
|
return ThaiTokenizer(cls, nlp)
|
|
|
|
|
|
class Thai(Language):
|
|
lang = "th"
|
|
Defaults = ThaiDefaults
|
|
|
|
def make_doc(self, text):
|
|
return self.tokenizer(text)
|
|
|
|
|
|
__all__ = ["Thai"]
|