ckipnlp 1.0.3

Description:

ckipnlp 1.0.3

CKIP CoreNLP Toolkit

Features

Sentence Segmentation
Word Segmentation
Part-of-Speech Tagging
Named-Entity Recognition
Constituency Parsing
Coreference Resolution



Git
https://github.com/ckiplab/ckipnlp



PyPI
https://pypi.org/project/ckipnlp



Documentation
https://ckipnlp.readthedocs.io/



Online Demo
https://ckip.iis.sinica.edu.tw/service/corenlp


Contributers

Mu Yang at CKIP (Author & Maintainer)
Wei-Yun Ma at CKIP (Maintainer)
DouglasWu




Installation

Requirements

Python 3.6+
TreeLib 1.5+
CkipTagger 0.2.1+ [Optional, Recommended]
CkipClassic 1.0+ [Optional, Recommended]
TensorFlow / TensorFlow-GPU 1.13.1+ [Required by CkipTagger]



Driver Requirements


Driver
Built-in
CkipTagger
CkipClassic



Sentence Segmentation
✔



Word Segmentation†

✔
✔

Part-of-Speech Tagging†

✔
✔

Constituency Parsing


✔

Named-Entity Recognition

✔


Coreference Resolution‡
✔
✔
✔




† These drivers require only one of either backends.
‡ Coreference implementation does not require any backend, but requires results from word segmentation, part-of-speech tagging, constituency parsing, and named-entity recognition.



Installation via Pip

No backend (not recommended): pip install ckipnlp.
With CkipTagger backend (recommended): pip install ckipnlp[tagger] or pip install ckipnlp[tagger-gpu].
With CkipClassic Parser Client backend (recommended): pip install ckipnlp[classic].
With CkipClassic offline backend: Please refer https://ckip-classic.readthedocs.io/en/latest/main/readme.html#installation for CkipClassic installation guide.


Attention!
To use CkipClassic Parser Client backend, please

Register an account at http://parser.iis.sinica.edu.tw/v1/reg.php
Set the username and password in the pipeline’s options:

pipeline = CkipPipeline(opts={'con_parser': {'username': YOUR_USERNAME, 'password': YOUR_PASSWORD})




Detail
See https://ckipnlp.readthedocs.io/ for full documentation.


License

Copyright (c) 2018-2023 CKIP Lab under the GPL-3.0 License.