mirror of
https://github.com/explosion/spaCy.git
synced 2024-09-22 03:49:17 +03:00
69 lines
2.3 KiB
Cython
69 lines
2.3 KiB
Cython
# cython: profile=True
|
|
# cython: embedsignature=True
|
|
'''Tokenize English text, using a scheme that differs from the Penn Treebank 3
|
|
scheme in several important respects:
|
|
|
|
* Whitespace is added as tokens, except for single spaces. e.g.,
|
|
|
|
>>> [w.string for w in EN.tokenize(u'\\nHello \\tThere')]
|
|
[u'\\n', u'Hello', u' ', u'\\t', u'There']
|
|
|
|
* Contractions are normalized, e.g.
|
|
|
|
>>> [w.string for w in EN.tokenize(u"isn't ain't won't he's")]
|
|
[u'is', u'not', u'are', u'not', u'will', u'not', u'he', u"__s"]
|
|
|
|
* Hyphenated words are split, with the hyphen preserved, e.g.:
|
|
|
|
>>> [w.string for w in EN.tokenize(u'New York-based')]
|
|
[u'New', u'York', u'-', u'based']
|
|
|
|
Other improvements:
|
|
|
|
* Email addresses, URLs, European-formatted dates and other numeric entities not
|
|
found in the PTB are tokenized correctly
|
|
* Heuristic handling of word-final periods (PTB expects sentence boundary detection
|
|
as a pre-process before tokenization.)
|
|
|
|
Take care to ensure your training and run-time data is tokenized according to the
|
|
same scheme. Tokenization problems are a major cause of poor performance for
|
|
NLP tools. If you're using a pre-trained model, the :py:mod:`spacy.ptb3` module
|
|
provides a fully Penn Treebank 3-compliant tokenizer.
|
|
'''
|
|
# TODO
|
|
#The script translate_treebank_tokenization can be used to transform a treebank's
|
|
#annotation to use one of the spacy tokenization schemes.
|
|
|
|
|
|
from __future__ import unicode_literals
|
|
|
|
cimport lang
|
|
from .typedefs cimport flags_t
|
|
import orth
|
|
|
|
|
|
cdef class English(Language):
|
|
"""English tokenizer, tightly coupled to lexicon.
|
|
|
|
Attributes:
|
|
name (unicode): The two letter code used by Wikipedia for the language.
|
|
lexicon (Lexicon): The lexicon. Exposes the lookup method.
|
|
"""
|
|
def set_flags(self, unicode string):
|
|
cdef flags_t flags = 0
|
|
flags |= orth.is_alpha(string) << IS_ALPHA
|
|
flags |= orth.is_ascii(string) << IS_ASCII
|
|
flags |= orth.is_digit(string) << IS_DIGIT
|
|
flags |= orth.is_lower(string) << IS_LOWER
|
|
flags |= orth.is_punct(string) << IS_PUNCT
|
|
flags |= orth.is_space(string) << IS_SPACE
|
|
flags |= orth.is_title(string) << IS_TITLE
|
|
flags |= orth.is_upper(string) << IS_UPPER
|
|
|
|
flags |= orth.like_url(string) << LIKE_URL
|
|
flags |= orth.like_number(string) << LIKE_NUMBER
|
|
return flags
|
|
|
|
|
|
EN = English('en')
|