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

• † 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.

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.