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CKIP CoreNLP

Project description

CKIP CoreNLP Toolkit

Features

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

Contributers

Installation

Requirements

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

  1. Register an account at http://parser.iis.sinica.edu.tw/v1/reg.exe
  2. 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

GPL-3.0

Copyright (c) 2018-2020 CKIP Lab under the GPL-3.0 License.

Project details


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