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]orpip 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.