repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/nn/tokenizer_exceptions.py | spacy/lang/nn/tokenizer_exceptions.py | from ...symbols import NORM, ORTH
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
_exc = {}
for exc_data in [
{ORTH: "jan.", NORM: "januar"},
{ORTH: "feb.", NORM: "februar"},
{ORTH: "mar.", NORM: "mars"},
{ORTH: "apr.", NORM: "april"},
{ORTH: "jun.", NORM: "juni"... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/nn/__init__.py | spacy/lang/nn/__init__.py | from ...language import BaseDefaults, Language
from ..nb import SYNTAX_ITERATORS
from .punctuation import TOKENIZER_INFIXES, TOKENIZER_PREFIXES, TOKENIZER_SUFFIXES
from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
class NorwegianNynorskDefaults(BaseDefaults):
tokenizer_exceptions = TOKENIZER_EXCEPTIONS
p... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/nn/punctuation.py | spacy/lang/nn/punctuation.py | from ..char_classes import (
ALPHA,
ALPHA_LOWER,
ALPHA_UPPER,
CONCAT_QUOTES,
CURRENCY,
LIST_CURRENCY,
LIST_ELLIPSES,
LIST_ICONS,
LIST_PUNCT,
LIST_QUOTES,
PUNCT,
UNITS,
)
from ..punctuation import TOKENIZER_SUFFIXES
_quotes = CONCAT_QUOTES.replace("'", "")
_list_punct = [... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/nn/examples.py | spacy/lang/nn/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.nn.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
# sentences taken from Omsetjingsminne frå Nynorsk pressekontor 2022 (https://www.nb.no/sprakbanken/en/resource-catalogue/oai-nb-no-sbr-80/)
sentences = [
"Konseptet går... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/mr/__init__.py | spacy/lang/mr/__init__.py | from ...language import BaseDefaults, Language
from .stop_words import STOP_WORDS
class MarathiDefaults(BaseDefaults):
stop_words = STOP_WORDS
class Marathi(Language):
lang = "mr"
Defaults = MarathiDefaults
__all__ = ["Marathi"]
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/mr/stop_words.py | spacy/lang/mr/stop_words.py | # Source: https://github.com/stopwords-iso/stopwords-mr/blob/master/stopwords-mr.txt, https://github.com/6/stopwords-json/edit/master/dist/mr.json
STOP_WORDS = set(
"""
न
अतरी
तो
हें
तें
कां
आणि
जें
जे
मग
ते
मी
जो
परी
गा
हे
ऐसें
आतां
नाहीं
तेथ
हा
तया
असे
म्हणे
काय
कीं
जैसें
तंव
तूं
होय
जैसा
आहे
पैं
तैसा
जरी
म्हणोनि... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ro/tokenizer_exceptions.py | spacy/lang/ro/tokenizer_exceptions.py | from ...symbols import ORTH
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
from .punctuation import _make_ro_variants
_exc = {}
# Source: https://en.wiktionary.org/wiki/Category:Romanian_abbreviations
for orth in [
"1-a",
"2-a",
"3-a",
"4-a",
"5-a",
"6-a",
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ro/__init__.py | spacy/lang/ro/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .punctuation import TOKENIZER_INFIXES, TOKENIZER_PREFIXES, TOKENIZER_SUFFIXES
from .stop_words import STOP_WORDS
from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
# Lemma data note:
# Original pairs downloaded from http://www.lex... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ro/punctuation.py | spacy/lang/ro/punctuation.py | import itertools
from ..char_classes import (
ALPHA,
ALPHA_LOWER,
ALPHA_UPPER,
CONCAT_QUOTES,
CURRENCY,
LIST_CURRENCY,
LIST_ELLIPSES,
LIST_ICONS,
LIST_PUNCT,
LIST_QUOTES,
PUNCT,
)
_list_icons = [x for x in LIST_ICONS if x != "°"]
_list_icons = [x.replace("\\u00B0", "") for ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ro/examples.py | spacy/lang/ro/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.ro import Romanian
>>> from spacy.lang.ro.examples import sentences
>>> nlp = Romanian()
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"Apple plănuiește să cumpere o companie britanică pentru un miliard de dolari",
"Municipali... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ro/lex_attrs.py | spacy/lang/ro/lex_attrs.py | from ...attrs import LIKE_NUM
_num_words = set(
"""
zero unu doi două trei patru cinci șase șapte opt nouă zece
unsprezece doisprezece douăsprezece treisprezece patrusprezece cincisprezece șaisprezece șaptesprezece optsprezece nouăsprezece
douăzeci treizeci patruzeci cincizeci șaizeci șaptezeci optzeci nouăzeci
su... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ro/stop_words.py | spacy/lang/ro/stop_words.py | # Source: https://github.com/stopwords-iso/stopwords-ro
STOP_WORDS = set(
"""
a
abia
acea
aceasta
această
aceea
aceeasi
aceeași
acei
aceia
acel
acela
acelasi
același
acele
acelea
acest
acesta
aceste
acestea
acestei
acestia
acestui
aceşti
aceştia
acolo
acord
acum
adica
adică
ai
aia
aibă
aici
aiurea
al
ala
alaturi
al... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ko/tag_map.py | spacy/lang/ko/tag_map.py | from ...symbols import (
ADJ,
ADP,
ADV,
AUX,
CONJ,
DET,
INTJ,
NOUN,
NUM,
POS,
PRON,
PROPN,
PUNCT,
SYM,
VERB,
X,
)
# 은전한닢(mecab-ko-dic)의 품사 태그를 universal pos tag로 대응시킴
# https://docs.google.com/spreadsheets/d/1-9blXKjtjeKZqsf4NzHeYJCrr49-nXeRF6D80udfcwY/ed... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ko/__init__.py | spacy/lang/ko/__init__.py | from typing import Any, Dict, Iterator
from ...language import BaseDefaults, Language
from ...scorer import Scorer
from ...symbols import POS, X
from ...tokens import Doc
from ...training import validate_examples
from ...util import DummyTokenizer, load_config_from_str, registry
from ...vocab import Vocab
from .lex_at... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ko/punctuation.py | spacy/lang/ko/punctuation.py | from ..char_classes import LIST_QUOTES
from ..punctuation import TOKENIZER_INFIXES as BASE_TOKENIZER_INFIXES
_infixes = (
["·", "ㆍ", r"\(", r"\)"]
+ [r"(?<=[0-9])~(?=[0-9-])"]
+ LIST_QUOTES
+ BASE_TOKENIZER_INFIXES
)
TOKENIZER_INFIXES = _infixes
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ko/examples.py | spacy/lang/ko/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.ko.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"애플이 영국의 스타트업을 10억 달러에 인수하는 것을 알아보고 있다.",
"자율주행 자동차의 손해 배상 책임이 제조 업체로 옮겨 가다",
"샌프란시스코 시가 자동 배달 로봇의 보도 주행 금지를 검토 중이라고 합니다.",
"런던은 영국의 수도이자 가장 큰 ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ko/lex_attrs.py | spacy/lang/ko/lex_attrs.py | from ...attrs import LIKE_NUM
_num_words = [
"영",
"공",
# Native Korean number system
"하나",
"둘",
"셋",
"넷",
"다섯",
"여섯",
"일곱",
"여덟",
"아홉",
"열",
"스물",
"서른",
"마흔",
"쉰",
"예순",
"일흔",
"여든",
"아흔",
# Sino-Korean number system
"일",
"이... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ko/stop_words.py | spacy/lang/ko/stop_words.py | STOP_WORDS = set(
"""
이
있
하
것
들
그
되
수
이
보
않
없
나
주
아니
등
같
때
년
가
한
지
오
말
일
그렇
위하
때문
그것
두
말하
알
그러나
받
못하
일
그런
또
더
많
그리고
좋
크
시키
그러
하나
살
데
안
어떤
번
나
다른
어떻
들
이렇
점
싶
말
좀
원
잘
놓
""".split()
)
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/is/__init__.py | spacy/lang/is/__init__.py | from ...language import BaseDefaults, Language
from .stop_words import STOP_WORDS
class IcelandicDefaults(BaseDefaults):
stop_words = STOP_WORDS
class Icelandic(Language):
lang = "is"
Defaults = IcelandicDefaults
__all__ = ["Icelandic"]
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/is/stop_words.py | spacy/lang/is/stop_words.py | # Source: https://github.com/Xangis/extra-stopwords
STOP_WORDS = set(
"""
afhverju
aftan
aftur
afþví
aldrei
allir
allt
alveg
annað
annars
bara
dag
eða
eftir
eiga
einhver
einhverjir
einhvers
eins
einu
eitthvað
ekkert
ekki
ennþá
eru
fara
fer
finna
fjöldi
fólk
framan
frá
frekar
fyrir
gegnum
geta
getur
gmg
gott
hann
h... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/id/_tokenizer_exceptions_list.py | spacy/lang/id/_tokenizer_exceptions_list.py | ID_BASE_EXCEPTIONS = set(
"""
aba-aba
abah-abah
abal-abal
abang-abang
abar-abar
abong-abong
abrit-abrit
abrit-abritan
abu-abu
abuh-abuhan
abuk-abuk
abun-abun
acak-acak
acak-acakan
acang-acang
acap-acap
aci-aci
aci-acian
aci-acinya
aco-acoan
ad-blocker
ad-interim
ada-ada
ada-adanya
ada-adanyakah
adang-adang
adap-ada... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | true |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/id/tokenizer_exceptions.py | spacy/lang/id/tokenizer_exceptions.py | from ...symbols import NORM, ORTH
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
from ._tokenizer_exceptions_list import ID_BASE_EXCEPTIONS
# Daftar singkatan dan Akronim dari:
# https://id.wiktionary.org/wiki/Wiktionary:Daftar_singkatan_dan_akronim_bahasa_Indonesia#A
_exc = {}
for... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/id/__init__.py | spacy/lang/id/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .punctuation import TOKENIZER_INFIXES, TOKENIZER_PREFIXES, TOKENIZER_SUFFIXES
from .stop_words import STOP_WORDS
from .syntax_iterators import SYNTAX_ITERATORS
from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
class IndonesianDe... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/id/punctuation.py | spacy/lang/id/punctuation.py | from ..char_classes import ALPHA, _currency, _units, merge_chars, split_chars
from ..punctuation import TOKENIZER_INFIXES, TOKENIZER_PREFIXES, TOKENIZER_SUFFIXES
_units = (
_units + "s bit Gbps Mbps mbps Kbps kbps ƒ ppi px "
"Hz kHz MHz GHz mAh "
"ratus rb ribu ribuan "
"juta jt jutaan mill?iar million... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/id/syntax_iterators.py | spacy/lang/id/syntax_iterators.py | from typing import Iterator, Tuple, Union
from ...errors import Errors
from ...symbols import NOUN, PRON, PROPN
from ...tokens import Doc, Span
def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Tuple[int, int, int]]:
"""
Detect base noun phrases from a dependency parse. Works on both Doc and Span.
"... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/id/examples.py | spacy/lang/id/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.id.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"Indonesia merupakan negara kepulauan yang kaya akan budaya.",
"Berapa banyak warga yang dibutuhkan saat kerja bakti?",
"Penyaluran pupuk berasal d... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/id/lex_attrs.py | spacy/lang/id/lex_attrs.py | import unicodedata
from ...attrs import IS_CURRENCY, LIKE_NUM
from .punctuation import LIST_CURRENCY
_num_words = [
"nol",
"satu",
"dua",
"tiga",
"empat",
"lima",
"enam",
"tujuh",
"delapan",
"sembilan",
"sepuluh",
"sebelas",
"belas",
"puluh",
"ratus",
"r... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/id/stop_words.py | spacy/lang/id/stop_words.py | STOP_WORDS = set(
"""
ada adalah adanya adapun agak agaknya agar akan akankah akhir akhiri akhirnya
aku akulah amat amatlah anda andalah antar antara antaranya apa apaan apabila
apakah apalagi apatah artinya asal asalkan atas atau ataukah ataupun awal
awalnya
bagai bagaikan bagaimana bagaimanakah bagaimanapun bagi... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/gu/__init__.py | spacy/lang/gu/__init__.py | from ...language import BaseDefaults, Language
from .stop_words import STOP_WORDS
class GujaratiDefaults(BaseDefaults):
stop_words = STOP_WORDS
class Gujarati(Language):
lang = "gu"
Defaults = GujaratiDefaults
__all__ = ["Gujarati"]
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/gu/examples.py | spacy/lang/gu/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.gu.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"લોકશાહી એ સરકારનું એક એવું તંત્ર છે જ્યાં નાગરિકો મત દ્વારા સત્તાનો ઉપયોગ કરે છે.",
"તે ગુજરાત રાજ્યના ધરમપુર શહેરમાં આવેલું હતું",
"કર્ણદેવ પહેલો... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/gu/stop_words.py | spacy/lang/gu/stop_words.py | STOP_WORDS = set(
"""
એમ
આ
એ
રહી
છે
છો
હતા
હતું
હતી
હોય
હતો
શકે
તે
તેના
તેનું
તેને
તેની
તેઓ
તેમને
તેમના
તેમણે
તેમનું
તેમાં
અને
અહીં
થી
થઈ
થાય
જે
ને
કે
ના
ની
નો
ને
નું
શું
માં
પણ
પર
જેવા
જેવું
જાય
જેમ
જેથી
માત્ર
માટે
પરથી
આવ્યું
એવી
આવી
રીતે
સુધી
થાય
થઈ
સાથે
લાગે
હોવા
છતાં
રહેલા
કરી
કરે
કેટલા
કોઈ
કેમ
કર્યો
કર્યુ
કર... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/fa/tokenizer_exceptions.py | spacy/lang/fa/tokenizer_exceptions.py | from ...symbols import NORM, ORTH
TOKENIZER_EXCEPTIONS = {
".ق ": [{ORTH: ".ق "}],
".م": [{ORTH: ".م"}],
".هـ": [{ORTH: ".هـ"}],
"ب.م": [{ORTH: "ب.م"}],
"ق.م": [{ORTH: "ق.م"}],
"آبرویت": [{ORTH: "آبروی", NORM: "آبروی"}, {ORTH: "ت", NORM: "ت"}],
"آبنباتش": [{ORTH: "آبنبات", NORM: "آبنبات"... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | true |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/fa/generate_verbs_exc.py | spacy/lang/fa/generate_verbs_exc.py | verb_roots = """
#هست
آخت#آهنج
آراست#آرا
آراماند#آرامان
آرامید#آرام
آرمید#آرام
آزرد#آزار
آزمود#آزما
آسود#آسا
آشامید#آشام
آشفت#آشوب
آشوبید#آشوب
آغازید#آغاز
آغشت#آمیز
آفرید#آفرین
آلود#آلا
آمد#آ
آمرزید#آمرز
آموخت#آموز
آموزاند#آموزان
آمیخت#آمیز
آورد#آر
آورد#آور
آویخت#آویز
آکند#آکن
آگاهانید#آگاهان
ارزید#ارز
افتاد#افت
افراخت... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/fa/__init__.py | spacy/lang/fa/__init__.py | from typing import Callable, Optional
from thinc.api import Model
from ...language import BaseDefaults, Language
from ...pipeline import Lemmatizer
from .lex_attrs import LEX_ATTRS
from .punctuation import TOKENIZER_SUFFIXES
from .stop_words import STOP_WORDS
from .syntax_iterators import SYNTAX_ITERATORS
from .token... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/fa/punctuation.py | spacy/lang/fa/punctuation.py | from ..char_classes import (
ALPHA_UPPER,
CURRENCY,
LIST_ELLIPSES,
LIST_PUNCT,
LIST_QUOTES,
UNITS,
)
_suffixes = (
LIST_PUNCT
+ LIST_ELLIPSES
+ LIST_QUOTES
+ [
r"(?<=[0-9])\+",
r"(?<=[0-9])%", # 4% -> ["4", "%"]
# Persian is written from Right-To-Left
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/fa/syntax_iterators.py | spacy/lang/fa/syntax_iterators.py | from typing import Iterator, Tuple, Union
from ...errors import Errors
from ...symbols import NOUN, PRON, PROPN
from ...tokens import Doc, Span
def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Tuple[int, int, int]]:
"""
Detect base noun phrases from a dependency parse. Works on both Doc and Span.
"... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/fa/examples.py | spacy/lang/fa/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.fa.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"این یک جمله نمونه می باشد.",
"قرار ما، امروز ساعت ۲:۳۰ بعدازظهر هست!",
"دیروز علی به من ۲۰۰۰.۱﷼ پول نقد داد.",
"چطور میتوان از تهران به کاشان... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/fa/lex_attrs.py | spacy/lang/fa/lex_attrs.py | from ...attrs import LIKE_NUM
MIM = "م"
ZWNJ_O_MIM = "ام"
YE_NUN = "ین"
_num_words = set(
"""
صفر
یک
دو
سه
چهار
پنج
شش
شیش
هفت
هشت
نه
ده
یازده
دوازده
سیزده
چهارده
پانزده
پونزده
شانزده
شونزده
هفده
هجده
هیجده
نوزده
بیست
سی
چهل
پنجاه
شصت
هفتاد
هشتاد
نود
صد
یکصد
یکصد
دویست
سیصد
چهارصد
پانصد
پونصد
ششصد
شیشصد
هفتصد
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/fa/stop_words.py | spacy/lang/fa/stop_words.py | # Stop words from HAZM package
STOP_WORDS = set(
"""
و
در
به
از
که
این
را
با
است
برای
آن
یک
خود
تا
کرد
بر
هم
نیز
گفت
میشود
وی
شد
دارد
ما
اما
یا
شده
باید
هر
آنها
بود
او
دیگر
دو
مورد
میکند
شود
کند
وجود
بین
پیش
شدهاست
پس
نظر
اگر
همه
یکی
حال
هستند
من
کنند
نیست
باشد
چه
بی
می
بخش
میکنند
همین
افزود
هایی
دارند
راه
همچن... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/am/tokenizer_exceptions.py | spacy/lang/am/tokenizer_exceptions.py | from ...symbols import NORM, ORTH
_exc = {}
for exc_data in [
{ORTH: "ት/ቤት"},
{ORTH: "ወ/ሮ", NORM: "ወይዘሮ"},
]:
_exc[exc_data[ORTH]] = [exc_data]
for orth in [
"ዓ.ም.",
"ኪ.ሜ.",
]:
_exc[orth] = [{ORTH: orth}]
TOKENIZER_EXCEPTIONS = _exc
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/am/__init__.py | spacy/lang/am/__init__.py | from ...attrs import LANG
from ...language import BaseDefaults, Language
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
from .lex_attrs import LEX_ATTRS
from .punctuation import TOKENIZER_SUFFIXES
from .stop_words import STOP_WORDS
from .tokenizer_exceptions import TOKENIZER_EXCEPTION... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/am/punctuation.py | spacy/lang/am/punctuation.py | from ..char_classes import (
ALPHA_UPPER,
CURRENCY,
LIST_ELLIPSES,
LIST_PUNCT,
LIST_QUOTES,
UNITS,
)
_list_punct = LIST_PUNCT + "፡ ። ፣ ፤ ፥ ፦ ፧ ፠ ፨".strip().split()
_suffixes = (
_list_punct
+ LIST_ELLIPSES
+ LIST_QUOTES
+ [
r"(?<=[0-9])\+",
# Amharic is written ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/am/examples.py | spacy/lang/am/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.am.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"አፕል የዩኬን ጅምር ድርጅት በ 1 ቢሊዮን ዶላር ለመግዛት አስቧል።",
"የራስ ገዝ መኪኖች የኢንሹራንስ ኃላፊነትን ወደ አምራቾች ያዛውራሉ",
"ሳን ፍራንሲስኮ የእግረኛ መንገድ አቅርቦት ሮቦቶችን ማገድን ይመለከታል",
"ለንደ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/am/lex_attrs.py | spacy/lang/am/lex_attrs.py | from ...attrs import LIKE_NUM
_num_words = [
"ዜሮ",
"አንድ",
"ሁለት",
"ሶስት",
"አራት",
"አምስት",
"ስድስት",
"ሰባት",
"ስምት",
"ዘጠኝ",
"አስር",
"አስራ አንድ",
"አስራ ሁለት",
"አስራ ሶስት",
"አስራ አራት",
"አስራ አምስት",
"አስራ ስድስት",
"አስራ ሰባት",
"አስራ ስምንት",
"አስራ ዘጠኝ",
"ሃያ",
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/am/stop_words.py | spacy/lang/am/stop_words.py | # Stop words by Teshome Kassie http://etd.aau.edu.et/bitstream/handle/123456789/3315/Teshome%20Kassie.pdf?sequence=1&isAllowed=y
# Stop words by Tihitina Petros http://etd.aau.edu.et/bitstream/handle/123456789/3384/Tihitina%20Petros.pdf?sequence=1&isAllowed=y
STOP_WORDS = set(
"""
ግን አንቺ አንተ እናንተ ያንተ ያንቺ የናንተ ራስህን... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/dsb/__init__.py | spacy/lang/dsb/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .stop_words import STOP_WORDS
class LowerSorbianDefaults(BaseDefaults):
lex_attr_getters = LEX_ATTRS
stop_words = STOP_WORDS
class LowerSorbian(Language):
lang = "dsb"
Defaults = LowerSorbianDefaults
__all__ = ["L... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/dsb/examples.py | spacy/lang/dsb/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.dsb.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"Z tym stwori so wuměnjenje a zakład za dalše wobdźěłanje přez analyzu tekstoweje struktury a semantisku anotaciju a z tym tež za tu předstajenu digitalnu... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/dsb/lex_attrs.py | spacy/lang/dsb/lex_attrs.py | from ...attrs import LIKE_NUM
_num_words = [
"nul",
"jaden",
"jadna",
"jadno",
"dwa",
"dwě",
"tśi",
"tśo",
"styri",
"styrjo",
"pěś",
"pěśo",
"šesć",
"šesćo",
"sedym",
"sedymjo",
"wósym",
"wósymjo",
"źewjeś",
"źewjeśo",
"źaseś",
"źa... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/dsb/stop_words.py | spacy/lang/dsb/stop_words.py | STOP_WORDS = set(
"""
a abo aby ako ale až
daniž dokulaž
gaž
jolic
pak pótom
teke togodla
""".split()
)
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/hi/__init__.py | spacy/lang/hi/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .stop_words import STOP_WORDS
class HindiDefaults(BaseDefaults):
stop_words = STOP_WORDS
lex_attr_getters = LEX_ATTRS
class Hindi(Language):
lang = "hi"
Defaults = HindiDefaults
__all__ = ["Hindi"]
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/hi/examples.py | spacy/lang/hi/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.hi.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"एप्पल 1 अरब डॉलर के लिए यू.के. स्टार्टअप खरीदने पर विचार कर रहा है।",
"स्वायत्त कारें निर्माताओं की ओर बीमा दायित्व रखतीं हैं।",
"सैन फ्रांसिस्को ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/hi/lex_attrs.py | spacy/lang/hi/lex_attrs.py | from ...attrs import LIKE_NUM, NORM
from ..norm_exceptions import BASE_NORMS
# fmt: off
_stem_suffixes = [
["ो", "े", "ू", "ु", "ी", "ि", "ा"],
["कर", "ाओ", "िए", "ाई", "ाए", "ने", "नी", "ना", "ते", "ीं", "ती", "ता", "ाँ", "ां", "ों", "ें"],
["ाकर", "ाइए", "ाईं", "ाया", "ेगी", "ेगा", "ोगी", "ोगे", "ाने", "... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/hi/stop_words.py | spacy/lang/hi/stop_words.py | # Source: https://github.com/taranjeet/hindi-tokenizer/blob/master/stopwords.txt, https://data.mendeley.com/datasets/bsr3frvvjc/1#file-a21d5092-99d7-45d8-b044-3ae9edd391c6
STOP_WORDS = set(
"""
अंदर
अत
अदि
अप
अपना
अपनि
अपनी
अपने
अभि
अभी
अंदर
आदि
आप
अगर
इंहिं
इंहें
इंहों
इतयादि
इत्यादि
इन
इनका
इन्हीं
इन्हें
इन्हों
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ru/tokenizer_exceptions.py | spacy/lang/ru/tokenizer_exceptions.py | from ...symbols import NORM, ORTH
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
_exc = {}
_abbrev_exc = [
# Weekdays abbreviations
{ORTH: "пн", NORM: "понедельник"},
{ORTH: "вт", NORM: "вторник"},
{ORTH: "ср", NORM: "среда"},
{ORTH: "чт", NORM: "четверг"},
{... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ru/lemmatizer.py | spacy/lang/ru/lemmatizer.py | from typing import Callable, Dict, List, Optional, Tuple
from thinc.api import Model
from ...pipeline import Lemmatizer
from ...pipeline.lemmatizer import lemmatizer_score
from ...symbols import POS
from ...tokens import Token
from ...vocab import Vocab
PUNCT_RULES = {"«": '"', "»": '"'}
class RussianLemmatizer(Le... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ru/__init__.py | spacy/lang/ru/__init__.py | from typing import Callable, Optional
from thinc.api import Model
from ...language import BaseDefaults, Language
from ..punctuation import (
COMBINING_DIACRITICS_TOKENIZER_INFIXES,
COMBINING_DIACRITICS_TOKENIZER_SUFFIXES,
)
from .lemmatizer import RussianLemmatizer
from .lex_attrs import LEX_ATTRS
from .stop_... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ru/examples.py | spacy/lang/ru/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.ru.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
# Translations from English:
"Apple рассматривает возможность покупки стартапа из Соединённого Королевства за $1 млрд",
"Беспилотные автомобили пер... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ru/lex_attrs.py | spacy/lang/ru/lex_attrs.py | from ...attrs import LIKE_NUM
_num_words = list(
set(
"""
ноль ноля нолю нолём ноле нулевой нулевого нулевому нулевым нулевом нулевая нулевую нулевое нулевые нулевых нулевыми
четверть четверти четвертью четвертей четвертям четвертями четвертях
треть трети третью третей третям третями третях
половина ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ru/stop_words.py | spacy/lang/ru/stop_words.py | STOP_WORDS = set(
"""
а авось ага агу аж ай али алло ау ах ая
б будем будет будете будешь буду будут будучи будь будьте бы был была были было
быть бац без безусловно бишь благо благодаря ближайшие близко более больше
будто бывает бывала бывали бываю бывают бытует
в вам вами вас весь во вот все всё всего всей всем... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/gd/tokenizer_exceptions.py | spacy/lang/gd/tokenizer_exceptions.py | from ...symbols import NORM, ORTH
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
"""
All rules and exceptions were taken from the "Gaelic Orthographic Conventions
of 2009" (GOC) and from the "Annotated Reference Corpus of Scottish Gaelic" (ARCOSG). I did
my best to ensure this token... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/gd/__init__.py | spacy/lang/gd/__init__.py | from typing import Optional
from ...language import BaseDefaults, Language
from .stop_words import STOP_WORDS
from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
class ScottishDefaults(BaseDefaults):
tokenizer_exceptions = TOKENIZER_EXCEPTIONS
stop_words = STOP_WORDS
class Scottish(Language):
lang =... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/gd/stop_words.py | spacy/lang/gd/stop_words.py | STOP_WORDS = set(
"""
'ad
'ar
'd # iad
'g # ag
'ga
'gam
'gan
'gar
'gur
'm # am
'n # an
'n seo
'na
'nad
'nam
'nan
'nar
'nuair
'nur
's
'sa
'san
'sann
'se
'sna
a
a'
a'd # agad
a'm # agam
a-chèile
a-seo
a-sin
a-siud
a chionn
a chionn 's
a chèile
a chéile
a dh'
a h-uile
a seo
ac' # aca
aca
aca-san
acasan
ach
ag
agad
aga... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ga/tokenizer_exceptions.py | spacy/lang/ga/tokenizer_exceptions.py | from ...symbols import NORM, ORTH
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
_exc = {
"'acha'n": [{ORTH: "'ach", NORM: "gach"}, {ORTH: "a'n", NORM: "aon"}],
"dem'": [{ORTH: "de", NORM: "de"}, {ORTH: "m'", NORM: "mo"}],
"ded'": [{ORTH: "de", NORM: "de"}, {ORTH: "d'", N... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ga/lemmatizer.py | spacy/lang/ga/lemmatizer.py | from typing import Dict, List, Tuple
from ...pipeline import Lemmatizer
from ...tokens import Token
class IrishLemmatizer(Lemmatizer):
# This is a lookup-based lemmatiser using data extracted from
# BuNaMo (https://github.com/michmech/BuNaMo)
@classmethod
def get_lookups_config(cls, mode: str) -> Tu... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ga/__init__.py | spacy/lang/ga/__init__.py | from typing import Optional
from thinc.api import Model
from ...language import BaseDefaults, Language
from .lemmatizer import IrishLemmatizer
from .stop_words import STOP_WORDS
from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
class IrishDefaults(BaseDefaults):
tokenizer_exceptions = TOKENIZER_EXCEPTIONS
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ga/stop_words.py | spacy/lang/ga/stop_words.py | STOP_WORDS = set(
"""
a ach ag agus an aon ar arna as
ba beirt bhúr
caoga ceathair ceathrar chomh chuig chun cois céad cúig cúigear
daichead dar de deich deichniúr den dhá do don dtí dá dár dó
faoi faoin faoina faoinár fara fiche
gach gan go gur
haon hocht
i iad idir in ina ins inár is
le leis lena lenár
m... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/bo/__init__.py | spacy/lang/bo/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .stop_words import STOP_WORDS
class TibetanDefaults(BaseDefaults):
lex_attr_getters = LEX_ATTRS
stop_words = STOP_WORDS
class Tibetan(Language):
lang = "bo"
Defaults = TibetanDefaults
__all__ = ["Tibetan"]
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/bo/examples.py | spacy/lang/bo/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.bo.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"དོན་དུ་རྒྱ་མཚོ་བླ་མ་ཞེས་བྱ་ཞིང༌།",
"ཏཱ་ལའི་ཞེས་པ་ནི་སོག་སྐད་ཡིན་པ་དེ་བོད་སྐད་དུ་རྒྱ་མཚོའི་དོན་དུ་འཇུག",
"སོག་པོ་ཨལ་ཐན་རྒྱལ་པོས་རྒྱལ་དབང་བསོད་ནམས་ར... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/bo/lex_attrs.py | spacy/lang/bo/lex_attrs.py | from ...attrs import LIKE_NUM
# reference 1: https://en.wikipedia.org/wiki/Tibetan_numerals
_num_words = [
"ཀླད་ཀོར་",
"གཅིག་",
"གཉིས་",
"གསུམ་",
"བཞི་",
"ལྔ་",
"དྲུག་",
"བདུན་",
"བརྒྱད་",
"དགུ་",
"བཅུ་",
"བཅུ་གཅིག་",
"བཅུ་གཉིས་",
"བཅུ་གསུམ་",
"བཅུ་བཞི་",
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/bo/stop_words.py | spacy/lang/bo/stop_words.py | # Source: https://zenodo.org/records/10148636
STOP_WORDS = set(
"""
འི་
།
དུ་
གིས་
སོགས་
ཏེ
གི་
རྣམས་
ནི
ཀུན་
ཡི་
འདི
ཀྱི་
སྙེད་
པས་
གཞན་
ཀྱིས་
ཡི
ལ
ནི་
དང་
སོགས
ཅིང་
ར
དུ
མི་
སུ་
བཅས་
ཡོངས་
ལས
ཙམ་
གྱིས་
དེ་
ཡང་
མཐའ་དག་
ཏུ་
ཉིད་
ས
ཏེ་
གྱི་
སྤྱི
དེ
ཀ་
ཡིན་
ཞིང་
འདི་
རུང་
རང་
ཞིག་
སྟེ
སྟེ་
ན་རེ
ངམ
ཤིང་
དག་
ཏོ
རེ་
འང... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/la/tokenizer_exceptions.py | spacy/lang/la/tokenizer_exceptions.py | from ...symbols import ORTH
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
## TODO: Look into systematically handling u/v
_exc = {
"mecum": [{ORTH: "me"}, {ORTH: "cum"}],
"tecum": [{ORTH: "te"}, {ORTH: "cum"}],
"nobiscum": [{ORTH: "nobis"}, {ORTH: "cum"}],
"vobiscum":... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/la/__init__.py | spacy/lang/la/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .stop_words import STOP_WORDS
from .syntax_iterators import SYNTAX_ITERATORS
from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
class LatinDefaults(BaseDefaults):
tokenizer_exceptions = TOKENIZER_EXCEPTIONS
stop_words = S... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/la/syntax_iterators.py | spacy/lang/la/syntax_iterators.py | from typing import Iterator, Tuple, Union
from ...errors import Errors
from ...symbols import AUX, NOUN, PRON, PROPN, VERB
from ...tokens import Doc, Span
# NB: Modified from da on suggestion from https://github.com/explosion/spaCy/issues/7457#issuecomment-800349751 [PJB]
def noun_chunks(doclike: Union[Doc, Span]) ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/la/examples.py | spacy/lang/la/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.la.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
# > Caes. BG 1.1
# > Cic. De Amic. 1
# > V. Georg. 1.1-5
# > Gen. 1:1
# > Galileo, Sid. Nunc.
# > van Schurman, Opusc. arg. 1
sentences = [
"Gallia est omnis divisa in ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/la/lex_attrs.py | spacy/lang/la/lex_attrs.py | import re
from ...attrs import LIKE_NUM
# cf. Goyvaerts/Levithan 2009; case-insensitive, allow 4
roman_numerals_compile = re.compile(
r"(?i)^(?=[MDCLXVI])M*(C[MD]|D?C{0,4})(X[CL]|L?X{0,4})(I[XV]|V?I{0,4})$"
)
_num_words = """unus una unum duo duae tres tria quattuor quinque sex septem octo novem decem undecim du... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/la/stop_words.py | spacy/lang/la/stop_words.py | # Corrected Perseus list, cf. https://wiki.digitalclassicist.org/Stopwords_for_Greek_and_Latin
STOP_WORDS = set(
"""
ab ac ad adhuc aliqui aliquis an ante apud at atque aut autem
cum cur
de deinde dum
ego enim ergo es est et etiam etsi ex
fio
haud hic
iam idem igitur ille in infra inter interim ipse is... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/hsb/tokenizer_exceptions.py | spacy/lang/hsb/tokenizer_exceptions.py | from ...symbols import NORM, ORTH
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
_exc = dict()
for exc_data in [
{ORTH: "mil.", NORM: "milion"},
{ORTH: "wob.", NORM: "wobydler"},
]:
_exc[exc_data[ORTH]] = [exc_data]
for orth in [
"resp.",
]:
_exc[orth] = [{ORTH: ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/hsb/__init__.py | spacy/lang/hsb/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .stop_words import STOP_WORDS
from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
class UpperSorbianDefaults(BaseDefaults):
lex_attr_getters = LEX_ATTRS
stop_words = STOP_WORDS
tokenizer_exceptions = TOKENIZER_EXCEPTIO... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/hsb/examples.py | spacy/lang/hsb/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.hsb.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"To běšo wjelgin raźone a jo se wót luźi derje pśiwzeło. Tak som dožywiła wjelgin",
"Jogo pśewóźowarce stej groniłej, až how w serbskich stronach njam... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/hsb/lex_attrs.py | spacy/lang/hsb/lex_attrs.py | from ...attrs import LIKE_NUM
_num_words = [
"nul",
"jedyn",
"jedna",
"jedne",
"dwaj",
"dwě",
"tři",
"třo",
"štyri",
"štyrjo",
"pjeć",
"šěsć",
"sydom",
"wosom",
"dźewjeć",
"dźesać",
"jědnaće",
"dwanaće",
"třinaće",
"štyrnaće",
"pjatnać... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/hsb/stop_words.py | spacy/lang/hsb/stop_words.py | STOP_WORDS = set(
"""
a abo ale ani
dokelž
hdyž
jeli jelizo
kaž
pak potom
tež tohodla
zo zoby
""".split()
)
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/sv/tokenizer_exceptions.py | spacy/lang/sv/tokenizer_exceptions.py | from ...symbols import NORM, ORTH
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
_exc = {}
# Verbs
for verb_data in [
{ORTH: "driver"},
{ORTH: "kör"},
{ORTH: "hörr"},
{ORTH: "fattar"},
{ORTH: "hajar"},
{ORTH: "lever"},
{ORTH: "serr"},
{ORTH: "fixar"... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/sv/__init__.py | spacy/lang/sv/__init__.py | from typing import Callable, Optional
from thinc.api import Model
from ...language import BaseDefaults, Language
from ...pipeline import Lemmatizer
from .lex_attrs import LEX_ATTRS
from .punctuation import TOKENIZER_INFIXES, TOKENIZER_SUFFIXES
from .stop_words import STOP_WORDS
from .syntax_iterators import SYNTAX_IT... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/sv/punctuation.py | spacy/lang/sv/punctuation.py | from ..char_classes import (
ALPHA,
ALPHA_LOWER,
ALPHA_UPPER,
CONCAT_QUOTES,
LIST_ELLIPSES,
LIST_ICONS,
)
from ..punctuation import TOKENIZER_SUFFIXES
_quotes = CONCAT_QUOTES.replace("'", "")
_infixes = (
LIST_ELLIPSES
+ LIST_ICONS
+ [
r"(?<=[{al}])\.(?=[{au}])".format(al=A... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/sv/syntax_iterators.py | spacy/lang/sv/syntax_iterators.py | from typing import Iterator, Tuple, Union
from ...errors import Errors
from ...symbols import NOUN, PRON, PROPN
from ...tokens import Doc, Span
def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Tuple[int, int, int]]:
"""Detect base noun phrases from a dependency parse. Works on Doc and Span."""
# fmt: o... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/sv/examples.py | spacy/lang/sv/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.sv.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"Apple överväger att köpa brittisk startup för 1 miljard dollar.",
"Självkörande bilar förskjuter försäkringsansvar mot tillverkare.",
"San Fransis... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/sv/lex_attrs.py | spacy/lang/sv/lex_attrs.py | from ...attrs import LIKE_NUM
_num_words = [
"noll",
"en",
"ett",
"två",
"tre",
"fyra",
"fem",
"sex",
"sju",
"åtta",
"nio",
"tio",
"elva",
"tolv",
"tretton",
"fjorton",
"femton",
"sexton",
"sjutton",
"arton",
"nitton",
"tjugo",
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/sv/stop_words.py | spacy/lang/sv/stop_words.py | STOP_WORDS = set(
"""
aderton adertonde adjö aldrig alla allas allt alltid alltså än andra andras
annan annat ännu artonde arton åtminstone att åtta åttio åttionde åttonde av
även
båda bådas bakom bara bäst bättre behöva behövas behövde behövt beslut beslutat
beslutit bland blev bli blir blivit bort borta bra
då ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/mk/tokenizer_exceptions.py | spacy/lang/mk/tokenizer_exceptions.py | from ...symbols import NORM, ORTH
_exc = {}
_abbr_exc = [
{ORTH: "м", NORM: "метар"},
{ORTH: "мм", NORM: "милиметар"},
{ORTH: "цм", NORM: "центиметар"},
{ORTH: "см", NORM: "сантиметар"},
{ORTH: "дм", NORM: "дециметар"},
{ORTH: "км", NORM: "километар"},
{ORTH: "кг", NORM: "килограм"},
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/mk/lemmatizer.py | spacy/lang/mk/lemmatizer.py | from collections import OrderedDict
from typing import List
from ...pipeline import Lemmatizer
from ...tokens import Token
class MacedonianLemmatizer(Lemmatizer):
def rule_lemmatize(self, token: Token) -> List[str]:
string = token.text
univ_pos = token.pos_.lower()
if univ_pos in ("", "e... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/mk/__init__.py | spacy/lang/mk/__init__.py | from typing import Callable, Optional
from thinc.api import Model
from ...attrs import LANG
from ...language import BaseDefaults, Language
from ...lookups import Lookups
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
from .lemmatizer import MacedonianLemmatizer
from .lex_attrs impor... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/mk/lex_attrs.py | spacy/lang/mk/lex_attrs.py | from ...attrs import LIKE_NUM
_num_words = [
"нула",
"еден",
"една",
"едно",
"два",
"две",
"три",
"четири",
"пет",
"шест",
"седум",
"осум",
"девет",
"десет",
"единаесет",
"дванаесет",
"тринаесет",
"четиринаесет",
"петнаесет",
"шеснаесет",
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/mk/stop_words.py | spacy/lang/mk/stop_words.py | STOP_WORDS = set(
"""
а
абре
aв
аи
ако
алало
ам
ама
аман
ами
амин
априли-ли-ли
ау
аух
ауч
ах
аха
аха-ха
аш
ашколсум
ашколсун
ај
ајде
ајс
аџаба
бавно
бам
бам-бум
бап
бар
баре
барем
бау
бау-бау
баш
бај
бе
беа
бев
бевме
бевте
без
безбели
бездруго
белки
беше
би
бидејќи
бим
бис
бла
блазе
богами
божем
боц
браво
бравос
бр... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/eu/__init__.py | spacy/lang/eu/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .punctuation import TOKENIZER_SUFFIXES
from .stop_words import STOP_WORDS
class BasqueDefaults(BaseDefaults):
suffixes = TOKENIZER_SUFFIXES
stop_words = STOP_WORDS
lex_attr_getters = LEX_ATTRS
class Basque(Language):
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/eu/punctuation.py | spacy/lang/eu/punctuation.py | from ..punctuation import TOKENIZER_SUFFIXES
_suffixes = TOKENIZER_SUFFIXES
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/eu/examples.py | spacy/lang/eu/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.eu.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"bilbon ko castinga egin da eta nik jakin ez zuetako inork egin al du edota parte hartu duen ezagunik ba al du",
"gaur telebistan entzunda denok martet... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/eu/lex_attrs.py | spacy/lang/eu/lex_attrs.py | from ...attrs import LIKE_NUM
# Source http://mylanguages.org/basque_numbers.php
_num_words = """
bat
bi
hiru
lau
bost
sei
zazpi
zortzi
bederatzi
hamar
hamaika
hamabi
hamahiru
hamalau
hamabost
hamasei
hamazazpi
Hemezortzi
hemeretzi
hogei
ehun
mila
milioi
""".split()
# source https://www.google.com/intl/ur/inputtool... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/eu/stop_words.py | spacy/lang/eu/stop_words.py | # Source: https://github.com/stopwords-iso/stopwords-eu
# https://www.ranks.nl/stopwords/basque
# https://www.mustgo.com/worldlanguages/basque/
STOP_WORDS = set(
"""
al
anitz
arabera
asko
baina
bat
batean
batek
bati
batzuei
batzuek
batzuetan
batzuk
bera
beraiek
berau
berauek
bere
berori
beroriek
beste
bezala
da
dag... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/lg/__init__.py | spacy/lang/lg/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .punctuation import TOKENIZER_INFIXES
from .stop_words import STOP_WORDS
class LugandaDefaults(BaseDefaults):
lex_attr_getters = LEX_ATTRS
infixes = TOKENIZER_INFIXES
stop_words = STOP_WORDS
class Luganda(Language):
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/lg/punctuation.py | spacy/lang/lg/punctuation.py | from ..char_classes import (
ALPHA,
ALPHA_LOWER,
ALPHA_UPPER,
CONCAT_QUOTES,
HYPHENS,
LIST_ELLIPSES,
LIST_ICONS,
)
_infixes = (
LIST_ELLIPSES
+ LIST_ICONS
+ [
r"(?<=[0-9])[+\-\*^](?=[0-9-])",
r"(?<=[{al}{q}])\.(?=[{au}{q}])".format(
al=ALPHA_LOWER, au... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
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