spaCy/spacy/lang/id/lex_attrs.py

43 lines
1.5 KiB
Python

# coding: utf8
from __future__ import unicode_literals
from ...attrs import LIKE_NUM
_num_words = ['zero', 'one', 'two', 'three', 'four', 'five', 'six', 'seven',
'eight', 'nine', 'ten', 'eleven', 'twelve', 'thirteen', 'fourteen',
'fifteen', 'sixteen', 'seventeen', 'eighteen', 'nineteen', 'twenty',
'thirty', 'forty', 'fifty', 'sixty', 'seventy', 'eighty', 'ninety',
'hundred', 'thousand', 'million', 'billion', 'trillion', 'quadrillion',
'gajillion', 'bazillion',
'nol', 'satu', 'dua', 'tiga', 'empat', 'lima', 'enam', 'tujuh',
'delapan', 'sembilan', 'sepuluh', 'sebelas', 'duabelas', 'tigabelas',
'empatbelas', 'limabelas', 'enambelas', 'tujuhbelas', 'delapanbelas',
'sembilanbelas', 'duapuluh', 'seratus', 'seribu', 'sejuta',
'ribu', 'rb', 'juta', 'jt', 'miliar', 'biliun', 'triliun',
'kuadriliun', 'kuintiliun', 'sekstiliun', 'septiliun', 'oktiliun',
'noniliun', 'desiliun',
]
def like_num(text):
text = text.replace(',', '').replace('.', '')
if text.isdigit():
return True
if text.count('/') == 1:
num, denom = text.split('/')
if num.isdigit() and denom.isdigit():
return True
if text in _num_words:
return True
if text.count('-') == 1:
pre, num = text.split('-')
if pre in ['Ke', 'ke'] and (num.isdigit() or num in _num_words):
return True
return False
LEX_ATTRS = {
LIKE_NUM: like_num
}