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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>
63 lines
1.5 KiB
Python
63 lines
1.5 KiB
Python
# coding: utf8
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from __future__ import unicode_literals
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from ...attrs import LIKE_NUM
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_num_words = [
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"ศูนย์",
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"หนึ่ง",
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"สอง",
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"สาม",
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"สี่",
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"ห้า",
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"หก",
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"เจ็ด",
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"แปด",
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"เก้า",
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"สิบ",
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"สิบเอ็ด",
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"ยี่สิบ",
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"ยี่สิบเอ็ด",
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"สามสิบ",
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"สามสิบเอ็ด",
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"สี่สิบ",
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"สี่สิบเอ็ด",
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"ห้าสิบ",
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"ห้าสิบเอ็ด",
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"หกสิบเอ็ด",
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"เจ็ดสิบ",
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"เจ็ดสิบเอ็ด",
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"แปดสิบ",
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"แปดสิบเอ็ด",
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"เก้าสิบ",
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"เก้าสิบเอ็ด",
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"ร้อย",
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"พัน",
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"ล้าน",
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"พันล้าน",
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"หมื่นล้าน",
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"แสนล้าน",
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"ล้านล้าน",
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"ล้านล้านล้าน",
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"ล้านล้านล้านล้าน",
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]
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def like_num(text):
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if text.startswith(("+", "-", "±", "~")):
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text = text[1:]
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text = text.replace(",", "").replace(".", "")
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if text.isdigit():
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return True
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if text.count("/") == 1:
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num, denom = text.split("/")
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if num.isdigit() and denom.isdigit():
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return True
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if text in _num_words:
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return True
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return False
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LEX_ATTRS = {LIKE_NUM: like_num}
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