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Armenian language support (#5246)
* add Armenian language and test cases * agreement submission
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106
.github/contributors/YohannesDatasci.md
vendored
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106
.github/contributors/YohannesDatasci.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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## Contributor Details
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| Field | Entry |
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|------------------------------- | -------------------- |
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| Name | Yohannes |
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| Company name (if applicable) | |
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| Title or role (if applicable) | |
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| Date | 2020-04-02 |
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| GitHub username | YohannesDatasci |
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| Website (optional) | |
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25
spacy/lang/hy/__init__.py
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25
spacy/lang/hy/__init__.py
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from .stop_words import STOP_WORDS
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from .lex_attrs import LEX_ATTRS
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from .tag_map import TAG_MAP
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from ...attrs import LANG
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from ...language import Language
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from ...tokens import Doc
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class ArmenianDefaults(Language.Defaults):
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lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
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lex_attr_getters[LANG] = lambda text: "hy"
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lex_attr_getters.update(LEX_ATTRS)
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stop_words = STOP_WORDS
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tag_map = TAG_MAP
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class Armenian(Language):
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lang = "hy"
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Defaults = ArmenianDefaults
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__all__ = ["Armenian"]
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16
spacy/lang/hy/examples.py
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16
spacy/lang/hy/examples.py
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from __future__ import unicode_literals
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"""
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Example sentences to test spaCy and its language models.
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>>> from spacy.lang.hy.examples import sentences
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>>> docs = nlp.pipe(sentences)
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"""
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sentences = [
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"Լոնդոնը Միացյալ Թագավորության մեծ քաղաք է։",
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"Ո՞վ է Ֆրանսիայի նախագահը։",
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"Որն է Միացյալ Նահանգների մայրաքաղաքը։",
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"Ե՞րբ է ծնվել Բարաք Օբաման։",
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]
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58
spacy/lang/hy/lex_attrs.py
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58
spacy/lang/hy/lex_attrs.py
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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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"զրօ",
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"մէկ",
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"երկու",
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"երեք",
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"չորս",
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"հինգ",
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"վեց",
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"յոթ",
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"ութ",
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"ինը",
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"տասը",
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"տասնմեկ",
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"տասներկու",
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"տասներեք",
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"տասնչորս",
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"տասնհինգ",
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"տասնվեց",
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"տասնյոթ",
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"տասնութ",
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"տասնինը",
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"քսան" "երեսուն",
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"քառասուն",
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"հիսուն",
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"վաթցսուն",
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"յոթանասուն",
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"ութսուն",
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"ինիսուն",
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"հարյուր",
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"հազար",
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"միլիոն",
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"միլիարդ",
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"տրիլիոն",
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"քվինտիլիոն",
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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.lower() 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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110
spacy/lang/hy/stop_words.py
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110
spacy/lang/hy/stop_words.py
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from __future__ import unicode_literals
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STOP_WORDS = set(
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"""
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նա
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ողջը
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այստեղ
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ենք
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նա
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էիր
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որպես
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ուրիշ
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բոլորը
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այն
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այլ
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նույնչափ
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էի
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մի
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և
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ողջ
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ես
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ոմն
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հետ
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նրանք
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ամենքը
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ըստ
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ինչ-ինչ
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այսպես
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համայն
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մի
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նաև
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նույնքան
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դա
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ովևէ
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համար
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այնտեղ
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էին
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որոնք
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սույն
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ինչ-որ
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ամենը
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նույնպիսի
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ու
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իր
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որոշ
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միևնույն
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ի
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այնպիսի
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մենք
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ամեն ոք
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նույն
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երբևէ
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այն
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որևէ
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ին
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այդպես
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նրա
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որը
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վրա
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դու
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էինք
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այդպիսի
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էիք
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յուրաքանչյուրը
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եմ
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պիտի
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այդ
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ամբողջը
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հետո
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եք
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ամեն
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այլ
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կամ
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այսքան
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որ
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այնպես
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այսինչ
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բոլոր
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է
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մեկնումեկը
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այդչափ
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այնքան
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ամբողջ
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երբևիցե
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այնչափ
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ամենայն
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մյուս
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այնինչ
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իսկ
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այդտեղ
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այս
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սա
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են
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ամեն ինչ
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որևիցե
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ում
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մեկը
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այդ
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դուք
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այսչափ
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այդքան
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այսպիսի
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էր
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յուրաքանչյուր
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այս
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մեջ
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թ
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""".split()
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)
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2478
spacy/lang/hy/tag_map.py
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2478
spacy/lang/hy/tag_map.py
Normal file
File diff suppressed because it is too large
Load Diff
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@ -234,3 +234,7 @@ def yo_tokenizer():
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def zh_tokenizer():
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pytest.importorskip("jieba")
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return get_lang_class("zh").Defaults.create_tokenizer()
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@pytest.fixture(scope="session")
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def hy_tokenizer():
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return get_lang_class("hy").Defaults.create_tokenizer()
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10
spacy/tests/lang/hy/test_text.py
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10
spacy/tests/lang/hy/test_text.py
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from __future__ import unicode_literals
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import pytest
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from spacy.lang.hy.lex_attrs import like_num
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@pytest.mark.parametrize("word", ["հիսուն"])
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def test_hy_lex_attrs_capitals(word):
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assert like_num(word)
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assert like_num(word.upper())
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47
spacy/tests/lang/hy/test_tokenizer.py
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47
spacy/tests/lang/hy/test_tokenizer.py
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from __future__ import unicode_literals
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import pytest
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# TODO add test cases with valid punctuation signs.
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hy_tokenize_text_test = [
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(
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"Մետաղագիտությունը պայմանականորեն բաժանվում է տեսականի և կիրառականի (տեխնիկական)",
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[
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"Մետաղագիտությունը",
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"պայմանականորեն",
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"բաժանվում",
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"է",
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"տեսականի",
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"և",
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"կիրառականի",
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"(",
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"տեխնիկական",
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")",
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],
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),
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(
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"Գետաբերանը գտնվում է Օմոլոնա գետի ձախ ափից 726 կմ հեռավորության վրա",
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[
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"Գետաբերանը",
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"գտնվում",
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"է",
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"Օմոլոնա",
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"գետի",
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"ձախ",
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"ափից",
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"726",
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"կմ",
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"հեռավորության",
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"վրա",
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],
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),
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]
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@pytest.mark.parametrize("text,expected_tokens", hy_tokenize_text_test)
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def test_ga_tokenizer_handles_exception_cases(hy_tokenizer, text, expected_tokens):
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tokens = hy_tokenizer(text)
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token_list = [token.text for token in tokens if not token.is_space]
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assert expected_tokens == token_list
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