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.github/contributors/phiedulxp.md
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.github/contributors/phiedulxp.md
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# spaCy contributor agreement
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This spaCy Contributor Agreement (**"SCA"**) is based on the
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[Oracle Contributor Agreement](http://www.oracle.com/technetwork/oca-405177.pdf).
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The SCA applies to any contribution that you make to any product or project
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managed by us (the **"project"**), and sets out the intellectual property rights
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you grant to us in the contributed materials. The term **"us"** shall mean
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[ExplosionAI GmbH](https://explosion.ai/legal). The term
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**"you"** shall mean the person or entity identified below.
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If you agree to be bound by these terms, fill in the information requested
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below and include the filled-in version with your first pull request, under the
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folder [`.github/contributors/`](/.github/contributors/). The name of the file
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should be your GitHub username, with the extension `.md`. For example, the user
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example_user would create the file `.github/contributors/example_user.md`.
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Read this agreement carefully before signing. These terms and conditions
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constitute a binding legal agreement.
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## Contributor Agreement
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1. The term "contribution" or "contributed materials" means any source code,
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object code, patch, tool, sample, graphic, specification, manual,
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documentation, or any other material posted or submitted by you to the project.
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2. With respect to any worldwide copyrights, or copyright applications and
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registrations, in your contribution:
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* you hereby assign to us joint ownership, and to the extent that such
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assignment is or becomes invalid, ineffective or unenforceable, you hereby
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grant to us a perpetual, irrevocable, non-exclusive, worldwide, no-charge,
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royalty-free, unrestricted license to exercise all rights under those
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copyrights. This includes, at our option, the right to sublicense these same
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rights to third parties through multiple levels of sublicensees or other
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licensing arrangements;
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* you agree that each of us can do all things in relation to your
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contribution as if each of us were the sole owners, and if one of us makes
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a derivative work of your contribution, the one who makes the derivative
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work (or has it made will be the sole owner of that derivative work;
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* you agree that you will not assert any moral rights in your contribution
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against us, our licensees or transferees;
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* you agree that we may register a copyright in your contribution and
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exercise all ownership rights associated with it; and
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* you agree that neither of us has any duty to consult with, obtain the
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consent of, pay or render an accounting to the other for any use or
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distribution of your contribution.
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3. With respect to any patents you own, or that you can license without payment
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to any third party, you hereby grant to us a perpetual, irrevocable,
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non-exclusive, worldwide, no-charge, royalty-free license to:
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* make, have made, use, sell, offer to sell, import, and otherwise transfer
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your contribution in whole or in part, alone or in combination with or
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included in any product, work or materials arising out of the project to
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which your contribution was submitted, and
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* at our option, to sublicense these same rights to third parties through
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multiple levels of sublicensees or other licensing arrangements.
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4. Except as set out above, you keep all right, title, and interest in your
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contribution. The rights that you grant to us under these terms are effective
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on the date you first submitted a contribution to us, even if your submission
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took place before the date you sign these terms.
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5. You covenant, represent, warrant and agree that:
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* Each contribution that you submit is and shall be an original work of
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authorship and you can legally grant the rights set out in this SCA;
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* to the best of your knowledge, each contribution will not violate any
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third party's copyrights, trademarks, patents, or other intellectual
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property rights; and
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* each contribution shall be in compliance with U.S. export control laws and
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other applicable export and import laws. You agree to notify us if you
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become aware of any circumstance which would make any of the foregoing
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representations inaccurate in any respect. We may publicly disclose your
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participation in the project, including the fact that you have signed the SCA.
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6. This SCA is governed by the laws of the State of California and applicable
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U.S. Federal law. Any choice of law rules will not apply.
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7. Please place an “x” on one of the applicable statement below. Please do NOT
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mark both statements:
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* [x] I am signing on behalf of myself as an individual and no other person
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or entity, including my employer, has or will have rights with respect to my
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contributions.
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* [ ] I am signing on behalf of my employer or a legal entity and I have the
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actual authority to contractually bind that entity.
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## Contributor Details
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| Field | Entry |
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|------------------------------- | -------------------- |
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| Name | Xiepeng Li |
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| Company name (if applicable) | |
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| Title or role (if applicable) | |
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| Date | 20190810 |
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| GitHub username | phiedulxp |
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| Website (optional) | |
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@ -6,7 +6,7 @@ from ...language import Language
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from ...tokens import Doc
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from ..tokenizer_exceptions import BASE_EXCEPTIONS
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from .stop_words import STOP_WORDS
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from .tag_map import TAG_MAP
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class ChineseDefaults(Language.Defaults):
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lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
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@ -14,6 +14,7 @@ class ChineseDefaults(Language.Defaults):
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use_jieba = True
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tokenizer_exceptions = BASE_EXCEPTIONS
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stop_words = STOP_WORDS
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tag_map = TAG_MAP
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writing_system = {"direction": "ltr", "has_case": False, "has_letters": False}
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@ -9,10 +9,12 @@ Example sentences to test spaCy and its language models.
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>>> docs = nlp.pipe(sentences)
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"""
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# from https://zh.wikipedia.org/wiki/汉语
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sentences = [
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"蘋果公司正考量用一億元買下英國的新創公司",
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"自駕車將保險責任歸屬轉移至製造商",
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"舊金山考慮禁止送貨機器人在人行道上行駛",
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"倫敦是英國的大城市",
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"作为语言而言，为世界使用人数最多的语言，目前世界有五分之一人口做为母语。",
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"汉语有多种分支，当中官话最为流行，为中华人民共和国的国家通用语言（又称为普通话）、以及中华民国的国语。",
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"此外，中文还是联合国正式语文，并被上海合作组织等国际组织采用为官方语言。",
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"在中国大陆，汉语通称为“汉语”。",
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"在联合国、台湾、香港及澳门，通称为“中文”。",
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"在新加坡及马来西亚，通称为“华语”。"
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]
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107
spacy/lang/zh/lex_attrs.py
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107
spacy/lang/zh/lex_attrs.py
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# coding: utf8
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from __future__ import unicode_literals
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import re
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from ...attrs import LIKE_NUM
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_single_num_words = [
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"〇",
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"一",
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"二",
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"三",
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"四",
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"五",
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"六",
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"七",
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"八",
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"九",
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"十",
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"十一",
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"十二",
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"十三",
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"十四",
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"十五",
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"十六",
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"十七",
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"十八",
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"十九",
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"廿",
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"卅",
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"卌",
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"皕",
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"零",
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"壹",
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"贰",
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"叁",
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"肆",
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"伍",
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"陆",
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"柒",
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"捌",
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"玖",
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"拾",
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"拾壹",
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"拾贰",
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"拾叁",
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"拾肆",
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"拾伍",
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"拾陆",
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"拾柒",
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"拾捌",
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"拾玖"
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]
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_count_num_words = [
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"一",
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"二",
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"三",
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"四",
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"五",
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"六",
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"七",
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"八",
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"九",
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"壹",
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"贰",
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"叁",
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"肆",
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"伍",
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"陆",
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"柒",
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"捌",
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"玖"
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]
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_base_num_words = [
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"十",
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"百",
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"千",
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"万",
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"亿",
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"兆",
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"拾",
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"佰",
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"仟"
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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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".", "").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 _single_num_words:
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return True
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if re.match('^((' + '|'.join(_count_num_words) + '){1}'
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+ '(' + '|'.join(_base_num_words) + '){1})+'
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+ '(' + '|'.join(_count_num_words) + ')?$', text):
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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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47
spacy/lang/zh/tag_map.py
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47
spacy/lang/zh/tag_map.py
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# coding: utf8
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from __future__ import unicode_literals
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from ...symbols import POS, PUNCT, SYM, ADJ, CONJ, CCONJ, NUM, DET, ADV, ADP, X, VERB
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from ...symbols import NOUN, PROPN, PART, INTJ, SPACE, PRON, AUX
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# The Chinese part-of-speech tagger uses the OntoNotes 5 version of the Penn Treebank tag set.
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# We also map the tags to the simpler Google Universal POS tag set.
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TAG_MAP = {
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"AS": {POS: PART},
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"DEC": {POS: PART},
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"DEG": {POS: PART},
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"DER": {POS: PART},
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"DEV": {POS: PART},
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"ETC": {POS: PART},
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"LC": {POS: PART},
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"MSP": {POS: PART},
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"SP": {POS: PART},
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"BA": {POS: X},
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"FW": {POS: X},
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"IJ": {POS: INTJ},
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"LB": {POS: X},
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"ON": {POS: X},
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"SB": {POS: X},
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"X": {POS: X},
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"URL": {POS: X},
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"INF": {POS: X},
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"NN": {POS: NOUN},
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"NR": {POS: NOUN},
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"NT": {POS: NOUN},
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"VA": {POS: VERB},
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"VC": {POS: VERB},
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"VE": {POS: VERB},
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"VV": {POS: VERB},
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"CD": {POS: NUM},
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"M": {POS: NUM},
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"OD": {POS: NUM},
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"DT": {POS: DET},
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"CC": {POS: CCONJ},
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"CS": {POS: CONJ},
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"AD": {POS: ADV},
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"JJ": {POS: ADJ},
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"P": {POS: ADP},
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"PN": {POS: PRON},
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"PU": {POS: PUNCT}
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}
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