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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

Git

https://github.com/ckiplab/ckipnlp

GitHub Version GitHub Release GitHub Issues

PyPI

https://pypi.org/project/ckipnlp

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Documentation

https://ckipnlp.readthedocs.io/

ReadTheDocs Home

Online Demo

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

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.

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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