Tokenizer POS-tagger Lemmatizer and Dependency-parser for modern and contemporary Japanese with BERT models

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Project links

Project description

SuPar-UniDic

Tokenizer, POS-tagger, lemmatizer, and dependency-parser for modern and contemporary Japanese with BERT models.

Basic usage

>>> import suparunidic
>>> nlp=suparunidic.load()
>>> doc=nlp("太郎は花子が読んでいる本を次郎に渡した")
>>> print(type(doc))
<class 'spacy.tokens.doc.Doc'>
>>> print(suparunidic.to_conllu(doc))
1	太郎	タロウ	PROPN	名詞-固有名詞-人名-名	_	12	nsubj	_	SpaceAfter=No|Translit=タロー
2	は	は	ADP	助詞-係助詞	_	1	case	_	SpaceAfter=No|Translit=ワ
3	花子	ハナコ	PROPN	名詞-固有名詞-人名-名	_	5	nsubj	_	SpaceAfter=No|Translit=ハナコ
4	が	が	ADP	助詞-格助詞	_	3	case	_	SpaceAfter=No|Translit=ガ
5	読ん	読む	VERB	動詞-一般	_	8	acl	_	SpaceAfter=No|Translit=ヨン
6	で	て	SCONJ	助詞-接続助詞	_	5	mark	_	SpaceAfter=No|Translit=デ
7	いる	居る	AUX	動詞-非自立可能	_	5	aux	_	SpaceAfter=No|Translit=イル
8	本	本	NOUN	名詞-普通名詞-一般	_	12	obj	_	SpaceAfter=No|Translit=ホン
9	を	を	ADP	助詞-格助詞	_	8	case	_	SpaceAfter=No|Translit=オ
10	次郎	ジロウ	PROPN	名詞-固有名詞-人名-名	_	12	obl	_	SpaceAfter=No|Translit=ジロー
11	に	に	ADP	助詞-格助詞	_	10	case	_	SpaceAfter=No|Translit=ニ
12	渡し	渡す	VERB	動詞-一般	_	0	root	_	SpaceAfter=No|Translit=ワタシ
13	た	た	AUX	助動詞	_	12	aux	_	SpaceAfter=No|Translit=タ

>>> 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)
>>> from deplacy.deprelja import deprelja
>>> for b in suparunidic.bunsetu_spans(doc):
...   for t in b.lefts:
...     print(suparunidic.bunsetu_span(t),"->",b,"("+deprelja[t.dep_]+")")
...
花子が -> 読んでいる (主語)
読んでいる -> 本を (連体修飾節)
太郎は -> 渡した (主語)
本を -> 渡した (目的語)
次郎に -> 渡した (斜格補語)

suparunidic.load(UniDic,BERT) loads a natural language processor pipeline, which uses UniDic for tokenizer POS-tagger and lemmatizer, then uses BERT for Biaffine dependency-parser of SuPar. Available UniDic options are:

UniDic="gendai": Use 現代書き言葉UniDic
UniDic="spoken": Use 現代話し言葉UniDic
UniDic="novel": Use 近現代口語小説UniDic.
UniDic="qkana": Use 旧仮名口語UniDic
UniDic="kindai": Use 近代文語UniDic
UniDic="kinsei": Use 近世江戸口語UniDic
UniDic="kyogen": Use 中世口語UniDic
UniDic="wakan": Use 中世文語UniDic
UniDic="wabun": Use 中古和文UniDic
UniDic="manyo": Use 上代語UniDic
UniDic=None unidic-lite (default)

Available BERT options are:

BERT="bert-japanese-aozora6m3m-unidic32k-2m" from bert-japanese-aozora (default)
BERT="roberta-large-japanese-aozora" from roberta-large-japanese-aozora
BERT="roberta-large-japanese-aozora-char" from roberta-large-japanese-aozora-char
BERT="roberta-base-japanese-aozora" from roberta-base-japanese-aozora
BERT="roberta-base-japanese-aozora-char" from roberta-base-japanese-aozora-char
BERT="roberta-small-japanese-aozora" from roberta-small-japanese-aozora
BERT="roberta-small-japanese-aozora-char" from roberta-small-japanese-aozora-char
BERT="deberta-large-japanese-aozora" from deberta-large-japanese-aozora
BERT="deberta-base-japanese-aozora" from deberta-base-japanese-aozora
BERT="deberta-small-japanese-aozora" from deberta-small-japanese-aozora
BERT="deberta-base-japanese-unidic" from deberta-base-japanese-aozora (fugashi required)
BERT="bert-base-japanese-char-extended" from bert-base-japanese-char-extended
BERT="bert-large-japanese-char-extended" from bert-large-japanese-char-extended
BERT="bert-base-japanese-char" from cl-tohoku (fugashi and ipadic required)
BERT="bert-base-japanese-whole-word-masking" from cl-tohoku (fugashi and ipadic required)
BERT="bert-large-japanese" from cl-tohoku (fugashi required)
BERT="bert-large-japanese-char" from cl-tohoku (fugashi required)
BERT="roberta-base-japanese" from nlp-waseda (SentencePiece required)
BERT="roberta-large-japanese" from nlp-waseda (SentencePiece required)
BERT="electra-base-japanese-discriminator" from izumi-lab (fugashi and ipadic required)
BERT="bert-small-japanese" from izumi-lab (fugashi and ipadic required)
BERT="electra-base-japanese-generator" from izumi-lab (fugashi and ipadic required)
BERT="japanese-roberta-base" from rinna (SentencePiece required)
BERT="albert-japanese-v2" from alinear-corp (SentencePiece required)
BERT="albert-base-japanese-v1" from ken11
BERT="electra-small-japanese-discriminator" from Cinnamon AI
BERT="electra-small-japanese-generator" from Cinnamon AI
BERT="ku-bert-japanese-large" from ku-bert-japanese
BERT="bert-base-ja-cased" from Geotrend
BERT="laboro-bert-japanese-large" from Laboro AI
BERT="nict-bert-base-japanese-100k" from NICT BERT
BERT="unihanlm-base" from microsoft/unihanlm-base
BERT="distilbert-base-japanese" from bandainamco-mirai

Installation for Linux

pip3 install suparunidic --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 suparunidic

Benchmarks

Results of 舞姬/雪國/荒野より-Benchmarks

BERT="bert-japanese-aozora6m3m-unidic32k-2m"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	84.91	74.07	77.78
UniDic="kindai"	74.77	69.09	69.09
UniDic="kinsei"	83.02	66.67	70.37

雪國	LAS	MLAS	BLEX
UniDic="qkana"	85.71	78.43	74.51
UniDic="kindai"	81.42	74.51	66.67
UniDic="kinsei"	78.95	67.92	64.15

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	74.35	56.00	56.00
UniDic="kindai"	74.35	53.33	53.33
UniDic="kinsei"	70.83	50.00	47.37

BERT="roberta-large-japanese-aozora"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	75.47	58.18	65.45
UniDic="kindai"	75.47	58.18	65.45
UniDic="kinsei"	66.67	52.63	56.14

雪國	LAS	MLAS	BLEX
UniDic="qkana"	87.50	82.35	78.43
UniDic="kindai"	83.19	78.43	74.51
UniDic="kinsei"	87.50	82.35	74.51

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	80.63	64.94	59.74
UniDic="kindai"	80.63	62.34	57.14
UniDic="kinsei"	78.12	59.74	54.55

BERT="roberta-large-japanese-aozora-char"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	79.25	69.09	76.36
UniDic="kindai"	79.25	69.09	76.36
UniDic="kinsei"	68.52	59.65	63.16

雪國	LAS	MLAS	BLEX
UniDic="qkana"	85.71	78.43	74.51
UniDic="kindai"	81.42	74.51	70.59
UniDic="kinsei"	85.71	78.43	70.59

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	76.44	61.33	61.33
UniDic="kindai"	76.44	61.33	61.33
UniDic="kinsei"	72.92	56.00	56.00

BERT="roberta-base-japanese-aozora"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	79.25	65.45	72.73
UniDic="kindai"	79.25	65.45	72.73
UniDic="kinsei"	68.52	60.71	64.29

雪國	LAS	MLAS	BLEX
UniDic="qkana"	87.50	82.35	78.43
UniDic="kindai"	83.19	78.43	74.51
UniDic="kinsei"	87.50	82.35	74.51

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	76.44	58.67	61.33
UniDic="kindai"	76.44	56.00	58.67
UniDic="kinsei"	73.96	53.33	56.00

BERT="roberta-base-japanese-aozora-char"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	83.02	70.37	77.78
UniDic="kindai"	83.02	70.37	77.78
UniDic="kinsei"	74.07	65.45	69.09

雪國	LAS	MLAS	BLEX
UniDic="qkana"	85.71	78.43	74.51
UniDic="kindai"	81.42	74.51	70.59
UniDic="kinsei"	85.71	78.43	70.59

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	76.44	57.89	57.89
UniDic="kindai"	76.44	55.26	55.26
UniDic="kinsei"	73.96	52.63	52.63

BERT="roberta-small-japanese-aozora"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	83.02	72.73	76.36
UniDic="kindai"	83.02	72.73	76.36
UniDic="kinsei"	70.37	60.71	64.29

雪國	LAS	MLAS	BLEX
UniDic="qkana"	85.71	78.43	74.51
UniDic="kindai"	81.42	74.51	70.59
UniDic="kinsei"	85.71	78.43	70.59

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	74.35	56.00	56.00
UniDic="kindai"	74.35	53.33	53.33
UniDic="kinsei"	71.88	50.67	50.67

BERT="roberta-small-japanese-aozora-char"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	77.36	65.45	72.73
UniDic="kindai"	77.36	65.45	72.73
UniDic="kinsei"	70.37	59.65	63.16

雪國	LAS	MLAS	BLEX
UniDic="qkana"	85.71	78.43	74.51
UniDic="kindai"	81.42	74.51	70.59
UniDic="kinsei"	85.71	78.43	70.59

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	73.30	53.33	53.33
UniDic="kindai"	73.30	50.67	50.67
UniDic="kinsei"	70.83	48.00	48.00

BERT="deberta-large-japanese-aozora"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	84.91	74.07	77.78
UniDic="kindai"	76.64	72.73	69.09
UniDic="kinsei"	81.13	66.67	70.37

雪國	LAS	MLAS	BLEX
UniDic="qkana"	85.71	78.43	74.51
UniDic="kindai"	81.42	74.51	66.67
UniDic="kinsei"	78.95	67.92	64.15

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	77.49	61.33	61.33
UniDic="kindai"	77.49	58.67	58.67
UniDic="kinsei"	73.96	55.26	52.63

BERT="deberta-base-japanese-aozora"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	86.79	77.78	77.78
UniDic="kindai"	76.64	72.73	69.09
UniDic="kinsei"	81.13	65.45	65.45

雪國	LAS	MLAS	BLEX
UniDic="qkana"	85.71	78.43	74.51
UniDic="kindai"	83.19	78.43	70.59
UniDic="kinsei"	78.95	67.92	64.15

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	72.25	53.33	53.33
UniDic="kindai"	72.25	50.67	50.67
UniDic="kinsei"	69.79	50.00	47.37

BERT="deberta-small-japanese-aozora"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	75.47	60.71	64.29
UniDic="kindai"	67.29	59.65	56.14
UniDic="kinsei"	71.70	50.91	54.55

雪國	LAS	MLAS	BLEX
UniDic="qkana"	83.93	74.51	70.59
UniDic="kindai"	79.65	70.59	62.75
UniDic="kinsei"	77.19	64.15	60.38

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	75.39	56.00	56.00
UniDic="kindai"	75.39	56.00	56.00
UniDic="kinsei"	71.88	52.63	50.00

BERT="deberta-base-japanese-unidic"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	86.79	77.78	77.78
UniDic="kindai"	76.64	72.73	69.09
UniDic="kinsei"	79.25	60.71	60.71

雪國	LAS	MLAS	BLEX
UniDic="qkana"	83.93	76.00	72.00
UniDic="kindai"	79.65	72.00	64.00
UniDic="kinsei"	77.19	65.38	61.54

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	77.49	61.33	61.33
UniDic="kindai"	77.49	58.67	58.67
UniDic="kinsei"	73.96	55.26	52.63

BERT="bert-base-japanese-char-extended"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	81.13	72.73	76.36
UniDic="kindai"	81.13	72.73	76.36
UniDic="kinsei"	68.52	59.65	63.16

雪國	LAS	MLAS	BLEX
UniDic="qkana"	85.71	78.43	74.51
UniDic="kindai"	81.42	74.51	70.59
UniDic="kinsei"	85.71	78.43	70.59

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	75.39	56.00	56.00
UniDic="kindai"	75.39	53.33	53.33
UniDic="kinsei"	71.88	48.00	48.00

BERT="bert-large-japanese-char-extended"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	75.47	64.29	71.43
UniDic="kindai"	75.47	64.29	71.43
UniDic="kinsei"	64.81	55.17	62.07

雪國	LAS	MLAS	BLEX
UniDic="qkana"	85.71	78.43	74.51
UniDic="kindai"	81.42	74.51	70.59
UniDic="kinsei"	85.71	78.43	70.59

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	78.53	64.00	64.00
UniDic="kindai"	78.53	61.33	61.33
UniDic="kinsei"	76.04	58.67	58.67

BERT="bert-base-japanese-char"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	77.36	64.29	71.43
UniDic="kindai"	77.36	64.29	71.43
UniDic="kinsei"	66.67	55.17	58.62

雪國	LAS	MLAS	BLEX
UniDic="qkana"	78.57	72.00	68.00
UniDic="kindai"	74.34	68.00	64.00
UniDic="kinsei"	78.57	72.00	64.00

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	75.39	58.67	58.67
UniDic="kindai"	75.39	56.00	56.00
UniDic="kinsei"	72.92	53.33	53.33

BERT="bert-base-japanese-whole-word-masking"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	73.58	57.14	64.29
UniDic="kindai"	73.58	57.14	64.29
UniDic="kinsei"	64.81	51.72	55.17

雪國	LAS	MLAS	BLEX
UniDic="qkana"	85.71	82.35	78.43
UniDic="kindai"	76.11	73.08	69.23
UniDic="kinsei"	85.71	82.35	74.51

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	73.30	52.63	52.63
UniDic="kindai"	73.30	52.63	52.63
UniDic="kinsei"	69.79	50.00	50.00

BERT="bert-large-japanese"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	79.25	65.45	72.73
UniDic="kindai"	79.25	65.45	72.73
UniDic="kinsei"	68.52	56.14	59.65

雪國	LAS	MLAS	BLEX
UniDic="qkana"	78.57	76.92	73.08
UniDic="kindai"	74.34	73.08	69.23
UniDic="kinsei"	78.57	76.92	69.23

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	78.53	59.74	57.14
UniDic="kindai"	78.53	57.14	54.55
UniDic="kinsei"	77.08	54.55	51.95

BERT="bert-large-japanese-char"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	79.25	69.09	72.73
UniDic="kindai"	79.25	69.09	72.73
UniDic="kinsei"	68.52	59.65	63.16

雪國	LAS	MLAS	BLEX
UniDic="qkana"	80.36	70.59	70.59
UniDic="kindai"	76.11	66.67	66.67
UniDic="kinsei"	80.36	70.59	66.67

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	74.35	53.33	53.33
UniDic="kindai"	74.35	50.67	50.67
UniDic="kinsei"	71.88	48.00	48.00

BERT="roberta-base-japanese"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	83.02	72.73	76.36
UniDic="kindai"	83.02	72.73	76.36
UniDic="kinsei"	72.22	63.16	66.67

雪國	LAS	MLAS	BLEX
UniDic="qkana"	85.71	78.43	74.51
UniDic="kindai"	83.19	78.43	74.51
UniDic="kinsei"	85.71	78.43	70.59

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	72.25	51.35	51.35
UniDic="kindai"	72.25	51.35	51.35
UniDic="kinsei"	69.79	48.65	48.65

BERT="roberta-large-japanese"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	79.25	65.45	69.09
UniDic="kindai"	69.16	60.71	57.14
UniDic="kinsei"	73.58	50.00	53.57

雪國	LAS	MLAS	BLEX
UniDic="qkana"	85.71	78.43	74.51
UniDic="kindai"	81.42	74.51	66.67
UniDic="kinsei"	78.95	67.92	64.15

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	72.25	57.89	57.89
UniDic="kindai"	72.25	55.26	55.26
UniDic="kinsei"	68.75	51.95	49.35

BERT="electra-base-japanese-discriminator"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	75.47	61.82	69.09
UniDic="kindai"	75.47	61.82	69.09
UniDic="kinsei"	64.81	52.63	56.14

雪國	LAS	MLAS	BLEX
UniDic="qkana"	87.50	82.35	78.43
UniDic="kindai"	83.19	78.43	74.51
UniDic="kinsei"	87.50	82.35	74.51

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	73.30	50.67	50.67
UniDic="kindai"	73.30	50.67	50.67
UniDic="kinsei"	70.83	48.00	48.00

BERT="bert-small-japanese"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	79.25	62.96	70.37
UniDic="kindai"	79.25	62.96	70.37
UniDic="kinsei"	70.37	57.14	60.71

雪國	LAS	MLAS	BLEX
UniDic="qkana"	76.79	73.08	69.23
UniDic="kindai"	72.57	69.23	65.38
UniDic="kinsei"	76.79	73.08	65.38

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	72.25	47.37	47.37
UniDic="kindai"	72.25	47.37	47.37
UniDic="kinsei"	69.79	42.67	45.33

BERT="electra-base-japanese-generator"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	77.36	64.29	71.43
UniDic="kindai"	77.36	64.29	71.43
UniDic="kinsei"	68.52	58.62	62.07

雪國	LAS	MLAS	BLEX
UniDic="qkana"	76.79	73.08	69.23
UniDic="kindai"	72.57	69.23	65.38
UniDic="kinsei"	76.79	73.08	65.38

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	69.11	45.33	45.33
UniDic="kindai"	69.11	45.33	45.33
UniDic="kinsei"	66.67	42.67	42.67

BERT="japanese-roberta-base"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	73.58	57.14	64.29
UniDic="kindai"	73.58	57.14	64.29
UniDic="kinsei"	64.81	51.72	55.17

雪國	LAS	MLAS	BLEX
UniDic="qkana"	87.50	82.35	78.43
UniDic="kindai"	83.19	78.43	74.51
UniDic="kinsei"	87.50	82.35	74.51

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	74.35	50.00	47.37
UniDic="kindai"	74.35	47.37	44.74
UniDic="kinsei"	71.88	44.74	42.11

BERT="albert-japanese-v2"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	77.36	64.29	71.43
UniDic="kindai"	77.36	64.29	71.43
UniDic="kinsei"	66.67	55.17	58.62

雪國	LAS	MLAS	BLEX
UniDic="qkana"	76.79	73.08	69.23
UniDic="kindai"	72.57	69.23	65.38
UniDic="kinsei"	76.79	73.08	65.38

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	73.30	51.95	49.35
UniDic="kindai"	73.30	49.35	46.75
UniDic="kinsei"	69.79	46.75	44.16

BERT="albert-base-japanese-v1"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	73.58	57.14	64.29
UniDic="kindai"	73.58	57.14	64.29
UniDic="kinsei"	64.81	51.72	55.17

雪國	LAS	MLAS	BLEX
UniDic="qkana"	76.79	73.08	69.23
UniDic="kindai"	74.34	69.23	65.38
UniDic="kinsei"	76.79	73.08	65.38

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	65.97	42.67	42.67
UniDic="kindai"	65.97	40.00	40.00
UniDic="kinsei"	64.58	39.47	39.47

BERT="electra-small-japanese-discriminator"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	73.58	57.14	64.29
UniDic="kindai"	73.58	57.14	64.29
UniDic="kinsei"	62.96	48.28	51.72

雪國	LAS	MLAS	BLEX
UniDic="qkana"	73.21	69.23	65.38
UniDic="kindai"	70.80	65.38	61.54
UniDic="kinsei"	73.21	69.23	61.54

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	74.35	50.00	47.37
UniDic="kindai"	74.35	50.00	47.37
UniDic="kinsei"	72.92	50.00	47.37

BERT="electra-small-japanese-generator"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	73.58	60.71	64.29
UniDic="kindai"	73.58	60.71	64.29
UniDic="kinsei"	66.67	55.17	58.62

雪國	LAS	MLAS	BLEX
UniDic="qkana"	73.21	69.23	65.38
UniDic="kindai"	70.80	65.38	61.54
UniDic="kinsei"	73.21	69.23	61.54

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	69.11	45.95	45.95
UniDic="kindai"	69.11	43.24	43.24
UniDic="kinsei"	66.67	40.54	40.54

BERT="ku-bert-japanese-large"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	77.36	65.45	72.73
UniDic="kindai"	77.36	65.45	72.73
UniDic="kinsei"	64.81	52.63	59.65

雪國	LAS	MLAS	BLEX
UniDic="qkana"	82.14	74.51	70.59
UniDic="kindai"	81.42	74.51	70.59
UniDic="kinsei"	82.14	74.51	66.67

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	62.83	39.47	42.11
UniDic="kindai"	62.83	36.84	39.47
UniDic="kinsei"	62.50	38.96	41.56

BERT="bert-base-ja-cased"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	73.58	58.18	65.45
UniDic="kindai"	73.58	58.18	65.45
UniDic="kinsei"	64.81	52.63	56.14

雪國	LAS	MLAS	BLEX
UniDic="qkana"	73.21	69.23	65.38
UniDic="kindai"	70.80	65.38	61.54
UniDic="kinsei"	73.21	69.23	61.54

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	63.87	41.56	44.16
UniDic="kindai"	63.87	38.96	41.56
UniDic="kinsei"	61.46	36.36	38.96

BERT="laboro-bert-japanese-large"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	71.70	56.14	63.16
UniDic="kindai"	71.70	56.14	63.16
UniDic="kinsei"	62.96	50.85	54.24

雪國	LAS	MLAS	BLEX
UniDic="qkana"	71.43	65.38	65.38
UniDic="kindai"	67.26	61.54	61.54
UniDic="kinsei"	71.43	65.38	61.54

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	67.02	42.67	42.67
UniDic="kindai"	67.02	40.00	40.00
UniDic="kinsei"	65.62	37.33	37.33

BERT="nict-bert-base-japanese-100k"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	67.92	49.12	52.63
UniDic="kindai"	67.92	49.12	52.63
UniDic="kinsei"	57.41	40.68	44.07

雪國	LAS	MLAS	BLEX
UniDic="qkana"	82.14	74.51	74.51
UniDic="kindai"	81.42	74.51	74.51
UniDic="kinsei"	82.14	74.51	70.59

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	68.06	41.10	43.84
UniDic="kindai"	68.06	38.36	41.10
UniDic="kinsei"	65.62	35.62	38.36

BERT="unihanlm-base"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	69.81	52.63	59.65
UniDic="kindai"	69.81	52.63	59.65
UniDic="kinsei"	61.11	47.46	50.85

雪國	LAS	MLAS	BLEX
UniDic="qkana"	85.71	78.43	78.43
UniDic="kindai"	79.65	70.59	70.59
UniDic="kinsei"	85.71	78.43	74.51

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	61.78	36.36	38.96
UniDic="kindai"	61.78	36.36	38.96
UniDic="kinsei"	60.42	36.36	38.96

BERT="distilbert-base-japanese"

舞姬	LAS	MLAS	BLEX
UniDic="qkana"	77.36	64.29	71.43
UniDic="kindai"	77.36	64.29	71.43
UniDic="kinsei"	68.52	58.62	62.07

雪國	LAS	MLAS	BLEX
UniDic="qkana"	73.21	69.23	65.38
UniDic="kindai"	70.80	65.38	61.54
UniDic="kinsei"	73.21	69.23	61.54

荒野より	LAS	MLAS	BLEX
UniDic="qkana"	63.87	34.67	40.00
UniDic="kindai"	63.87	32.00	37.33
UniDic="kinsei"	62.50	34.21	36.84

Author

Koichi Yasuoka (安岡孝一)

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This version

1.4.7

Feb 28, 2026

1.4.6

Jan 22, 2026

1.4.5

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Aug 30, 2025

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Jan 31, 2024

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Oct 24, 2023

1.4.0

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1.3.9

Apr 17, 2023

1.3.8

Jun 11, 2022

1.3.7

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1.3.6

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Dec 18, 2021

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Nov 7, 2021

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Nov 4, 2021

1.0.9

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Oct 26, 2021

1.0.7

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Sep 4, 2021

1.0.3

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Aug 27, 2021

0.9.9

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0.9.8

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0.9.7

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0.8.9

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0.8.8

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0.8.7

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0.8.6

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0.8.5

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0.8.4

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0.8.3

Mar 27, 2021

0.8.2

Mar 27, 2021

0.8.1

Mar 24, 2021

0.8.0

Mar 17, 2021

0.7.9

Mar 16, 2021

0.7.8

Mar 16, 2021

0.7.6

Mar 11, 2021

0.7.4

Mar 11, 2021

0.7.3

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0.7.0

Feb 23, 2021

0.6.9

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0.6.7

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0.6.6

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Feb 22, 2021

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0.6.1

Feb 22, 2021

0.6.0

Feb 22, 2021

0.5.4

Feb 22, 2021

0.5.3

Feb 22, 2021

0.5.2

Feb 21, 2021

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Feb 21, 2021

0.5.0

Feb 21, 2021

0.4.5

Feb 21, 2021

0.4.4

Feb 21, 2021

0.4.3

Feb 21, 2021

0.4.2

Feb 21, 2021

0.4.1

Feb 21, 2021

0.4.0

Feb 21, 2021

0.3.0

Feb 21, 2021

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suparunidic 1.4.7

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SuPar-UniDic

Basic usage

Installation for Linux

Installation for Cygwin64

Benchmarks

BERT="bert-japanese-aozora6m3m-unidic32k-2m"

BERT="roberta-large-japanese-aozora"

BERT="roberta-large-japanese-aozora-char"

BERT="roberta-base-japanese-aozora"

BERT="roberta-base-japanese-aozora-char"

BERT="roberta-small-japanese-aozora"

BERT="roberta-small-japanese-aozora-char"

BERT="deberta-large-japanese-aozora"

BERT="deberta-base-japanese-aozora"

BERT="deberta-small-japanese-aozora"

BERT="deberta-base-japanese-unidic"

BERT="bert-base-japanese-char-extended"

BERT="bert-large-japanese-char-extended"

BERT="bert-base-japanese-char"

BERT="bert-base-japanese-whole-word-masking"

BERT="bert-large-japanese"

BERT="bert-large-japanese-char"

BERT="roberta-base-japanese"

BERT="roberta-large-japanese"

BERT="electra-base-japanese-discriminator"

BERT="bert-small-japanese"

BERT="electra-base-japanese-generator"

BERT="japanese-roberta-base"

BERT="albert-japanese-v2"

BERT="albert-base-japanese-v1"

BERT="electra-small-japanese-discriminator"

BERT="electra-small-japanese-generator"

BERT="ku-bert-japanese-large"

BERT="bert-base-ja-cased"

BERT="laboro-bert-japanese-large"

BERT="nict-bert-base-japanese-100k"

BERT="unihanlm-base"

BERT="distilbert-base-japanese"

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