esupar

Tokenizer, POS-tagger, and dependency-parser with Transformers and SuPar.

Basic usage

>>> 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)

Metadata

Release files for esupar 1.9.4

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for esupar 1.9.4
File	Interpreter	ABI	Platform	Reset
esupar-1.9.4-py3-none-any.whl 148.1 kB Aug 31, 2026	Python 3	none	any	Details

Release files / esupar-1.9.4-py3-none-any.whl

Download URL	esupar-1.9.4-py3-none-any.whl
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