>>> import esupar
>>> nlp=esupar.load("ja")
>>> doc=nlp("太郎は花子が読んでいる本を次郎に渡した")
>>> print(doc)
1	太郎	_	PROPN	_	_	12	nsubj	_	SpaceAfter=No
2	は	_	ADP	_	_	1	case	_	SpaceAfter=No
3	花子	_	PROPN	_	_	5	nsubj	_	SpaceAfter=No
4	が	_	ADP	_	_	3	case	_	SpaceAfter=No
5	読ん	_	VERB	_	_	8	acl	_	SpaceAfter=No
6	で	_	SCONJ	_	_	5	mark	_	SpaceAfter=No
7	いる	_	AUX	_	_	5	aux	_	SpaceAfter=No
8	本	_	NOUN	_	_	12	obj	_	SpaceAfter=No
9	を	_	ADP	_	_	8	case	_	SpaceAfter=No
10	次郎	_	PROPN	_	_	12	obl	_	SpaceAfter=No
11	に	_	ADP	_	_	10	case	_	SpaceAfter=No
12	渡し	_	VERB	_	_	0	root	_	SpaceAfter=No
13	た	_	AUX	_	_	12	aux	_	_

>>> import deplacy
>>> deplacy.render(doc,Japanese=True)
太郎 PROPN ═╗<════════╗ nsubj(主語)
は   ADP   <╝         ║ case(格表示)
花子 PROPN ═╗<══╗     ║ nsubj(主語)
が   ADP   <╝   ║     ║ case(格表示)
読ん VERB  ═╗═╗═╝<╗   ║ acl(連体修飾節)
で   SCONJ <╝ ║   ║   ║ mark(標識)
いる AUX   <══╝   ║   ║ aux(動詞補助成分)
本   NOUN  ═╗═════╝<╗ ║ obj(目的語)
を   ADP   <╝       ║ ║ case(格表示)
次郎 PROPN ═╗<╗     ║ ║ obl(斜格補語)
に   ADP   <╝ ║     ║ ║ case(格表示)
渡し VERB  ═╗═╝═════╝═╝ root(親)
た   AUX   <╝           aux(動詞補助成分)

esupar.load(model) loads a natural language processor pipeline, working on Universal Dependencies. Available model options are:

model="ja" Japanese model bert-base-japanese-upos (default)
model="ja_large" Japanese model bert-large-japanese-upos
model="ja_luw_small" Japanese long-unit-word model roberta-small-japanese-char-luw-upos
model="ja_luw_base" Japanese long-unit-word model bert-base-japanese-luw-upos
model="ja_luw_large" Japanese long-unit-word model bert-large-japanese-luw-upos
model="ko" Korean model roberta-base-korean-upos
model="ko_large" Korean model roberta-large-korean-upos
model="ko_morph_base" Korean morpheme model roberta-base-korean-morph-upos
model="ko_morph_large" Korean morpheme model roberta-large-korean-morph-upos
model="zh" Chinese model chinese-bert-wwm-ext-upos
model="zh_base" Chinese model chinese-roberta-base-upos
model="zh_large" Chinese model chinese-roberta-large-upos
model="lzh" Classical Chinese model roberta-classical-chinese-base-upos
model="lzh_large" Classical Chinese model roberta-classical-chinese-large-upos
model="th" Thai model roberta-base-thai-spm-upos
model="vi" Vietnamese model bert-base-vietnamese-upos
model="en" English model roberta-base-english-upos
model="en_large" English model roberta-large-english-upos
model="de" German model bert-base-german-upos
model="de_large" German model bert-large-german-upos
model="sr" Serbian (Cyrillic and Latin) model gpt2-small-serbian-upos
model="sr_large" Serbian (Cyrillic and Latin) model gpt2-large-serbian-upos
model="cop" Coptic model roberta-base-coptic-upos
model="ain" Ainu model roberta-base-ainu-upos

Installation for Linux

pip3 install esupar --user

Installation for Cygwin64

Make sure to get python37-devel python37-pip python37-cython python37-numpy python37-wheel gcc-g++ mingw64-x86_64-gcc-g++ git curl make cmake, and then:

curl -L https://raw.githubusercontent.com/KoichiYasuoka/CygTorch/master/installer/supar.sh | sh
pip3.7 install esupar

Installation for Google Colaboratory

!pip install esupar

Try notebook.

Author

Koichi Yasuoka (安岡孝一)

分类

License :: OSI Approved :: MIT License Natural Language :: Chinese (Simplified) Natural Language :: Chinese (Traditional) Natural Language :: English Natural Language :: German Natural Language :: Japanese Natural Language :: Korean Natural Language :: Serbian Natural Language :: Thai Natural Language :: Vietnamese Operating System :: OS Independent Programming Language :: Python :: 3 Topic :: Text Processing :: Linguistic

版本列表

1.9.2 2026-02-28

1.9.1 2026-02-23

1.9.0 2026-01-22

1.8.9 2026-01-21

1.8.8 2025-08-31

1.8.7 2025-08-31

1.8.6 2025-08-30

1.8.5 2025-08-30

1.8.4 2025-08-30

1.8.3 2025-08-12

1.8.2 2025-04-13

1.8.1 2025-03-28

1.8.0 2025-03-28

1.7.9 2025-03-28

1.7.8 2025-03-27

1.7.7 2025-01-03

1.7.6 2024-11-28

1.7.5 2024-09-27

1.7.4 2024-09-12

1.7.3 2024-08-15

1.7.2 2024-05-20

1.7.1 2024-05-09

1.7.0 2024-02-29

1.6.9 2024-02-06

1.6.8 2024-01-10

1.6.7 2023-11-08

1.6.6 2023-11-05

1.6.5 2023-11-05

1.6.4 2023-07-17

1.6.3 2023-07-17

1.6.2 2023-02-18

1.6.1 2023-02-17

1.6.0 2023-02-13

1.5.9 2023-02-06

1.5.8 2023-02-04

1.5.7 2023-01-31

1.5.6 2023-01-27

1.5.5 2023-01-22

1.5.4 2023-01-21

1.5.3 2023-01-19

1.5.2 2023-01-17

1.5.1 2023-01-14

1.5.0 2023-01-10

1.4.9 2023-01-09

1.4.8 2023-01-04

1.4.7 2022-12-30

1.4.6 2022-12-30

1.4.5 2022-12-30

1.4.4 2022-12-24

1.4.3 2022-12-15

1.4.2 2022-12-12

1.4.1 2022-12-05

1.4.0 2022-11-30

1.3.9 2022-11-29

1.3.8 2022-09-16

1.3.7 2022-08-03

1.3.6 2022-08-03

1.3.5 2022-08-03

1.3.4 2022-07-17

1.3.3 2022-07-14

1.3.2 2022-06-26

1.3.1 2022-06-19

1.3.0 2022-05-24

1.2.9 2022-05-24

1.2.8 2022-05-23

1.2.7 2022-05-08

1.2.6 2022-05-07

1.2.5 2022-04-17

1.2.4 2022-04-12

1.2.3 2022-04-10

1.2.2 2022-04-09

1.2.1 2022-03-14

1.2.0 2022-03-13

1.1.9 2022-03-13

1.1.8 2022-03-11

1.1.7 2022-02-23

1.1.6 2022-02-21

1.1.5 2022-02-17

1.1.4 2022-02-16

1.1.3 2022-02-13

1.1.2 2022-02-10

1.1.1 2022-02-10

1.1.0 2022-02-10

1.0.9 2022-02-10

1.0.8 2022-02-09

1.0.7 2022-02-05

1.0.6 2022-02-05

1.0.5 2022-01-31

1.0.4 2022-01-20

1.0.3 2022-01-03

1.0.2 2022-01-03

1.0.1 2022-01-03

1.0.0 2022-01-01

0.9.9 2022-01-01

0.9.8 2021-12-31

0.9.7 2021-12-28

0.9.6 2021-12-23

0.9.5 2021-12-20

0.9.4 2021-12-18

0.9.3 2021-11-21

0.9.2 2021-11-05

0.9.1 2021-11-05

0.9.0 2021-11-03

0.8.3 2021-10-26

0.8.2 2021-10-26

0.8.1 2021-10-26

0.8.0 2021-10-23

0.7.6 2021-10-23

0.7.5 2021-10-23

0.7.4 2021-10-23

0.7.3 2021-10-23

0.7.2 2021-10-23

0.7.1 2021-10-23

0.7.0 2021-09-18

0.6.0 2021-09-18

0.5.0 2021-09-17