Skip to main content

Tokenizer POS-tagger and Dependency-parser for Classical Chinese

Project description

Current PyPI packages

UD-Kanbun

Tokenizer, POS-Tagger, and Dependency-Parser for Classical Chinese Texts (漢文/文言文), working on Universal Dependencies.

Basic usage

>>> import udkanbun
>>> lzh=udkanbun.load()
>>> s=lzh("不入虎穴不得虎子")
>>> print(s)
# text = 不入虎穴不得虎子
1			ADV	v,副詞,否定,無界	Polarity=Neg	2	advmod	_	Gloss=not|SpaceAfter=No
2			VERB	v,動詞,行為,移動	_	0	root	_	Gloss=enter|SpaceAfter=No
3			NOUN	n,名詞,主体,動物	_	4	nmod	_	Gloss=tiger|SpaceAfter=No
4			NOUN	n,名詞,固定物,地形	Case=Loc	2	obj	_	Gloss=cave|SpaceAfter=No
5			ADV	v,副詞,否定,無界	Polarity=Neg	6	advmod	_	Gloss=not|SpaceAfter=No
6			VERB	v,動詞,行為,得失	_	2	parataxis	_	Gloss=get|SpaceAfter=No
7			NOUN	n,名詞,主体,動物	_	8	nmod	_	Gloss=tiger|SpaceAfter=No
8			NOUN	n,名詞,,関係	_	6	obj	_	Gloss=child|SpaceAfter=No

>>> t=s[1]
>>> print(t.id,t.form,t.lemma,t.upos,t.xpos,t.feats,t.head.id,t.deprel,t.deps,t.misc)
1   ADV v,副詞,否定,無界 Polarity=Neg 2 advmod _ Gloss=not|SpaceAfter=No

>>> print(s.kaeriten())
虎穴虎子

>>> print(s.to_tree())
 <     advmod
 ─┴─┬─┐ root
 <   nmod
 ─┘<  obj
 <    advmod
 ─┴─┐< parataxis
 <    nmod
 ─┘<   obj

>>> f=open("trial.svg","w")
>>> f.write(s.to_svg())
>>> f.close()

trial.svg udkanbun.load() has two options udkanbun.load(MeCab=True,Danku=False). By default, the UD-Kanbun pipeline uses MeCab for tokenizer and POS-tagger, then uses UDPipe for dependency-parser. With the option MeCab=False the pipeline uses UDPipe for all through the processing. With the options MeCab=False,Danku=True the pipeline tries to segment sentences automatically.

udkanbun.UDKanbunEntry.to_tree() has an option to_tree(BoxDrawingWidth=2) for old terminals, whose Box Drawing characters are "fullwidth". to_tree(kaeriten=True,Japanese=True) is convenient for Japanese users.

You can simply use udkanbun on the command line:

echo 不入虎穴不得虎子 | udkanbun

Installation for Linux

Tar-ball is available for Linux, and is installed by default when you use pip:

pip install udkanbun

Installation for Cygwin

Make sure to get gcc-g++ python37-pip python37-devel packages, and then:

pip3.7 install udkanbun

Use python3.7 command in Cygwin instead of python.

Installation for Jupyter Notebook (Google Colaboratory)

!pip install udkanbun

Author

Koichi Yasuoka (安岡孝一)

References

Project details


Release history Release notifications | RSS feed

This version

1.8.6

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

udkanbun-1.8.6.tar.gz (10.3 MB view details)

Uploaded Source

File details

Details for the file udkanbun-1.8.6.tar.gz.

File metadata

  • Download URL: udkanbun-1.8.6.tar.gz
  • Upload date:
  • Size: 10.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.0 requests-toolbelt/0.8.0 tqdm/4.31.1 CPython/3.7.6

File hashes

Hashes for udkanbun-1.8.6.tar.gz
Algorithm Hash digest
SHA256 2f5fad9e3ec5ed6ba944d4ce553854fd122d3cf1ebba1deb267fad2c5e3b088d
MD5 64aa33e495caa39aadaaa5561ad1c7ae
BLAKE2b-256 5c3d17d388b4a2c49ce40a679f7d270ce667cfe31bd55bb250241f39a070f7b6

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page