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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.
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
Files:
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