This repository is a curated list of resources for Chinese Natural Language Processing (NLP), serving as a comprehensive guide for researchers, developers, and students interested in the field. It aims to consolidate tools, datasets, organizations, industry services, and learning materials related to Chinese NLP.

How It Works

The repository categorizes resources into logical sections, providing links and brief descriptions for each. This structured approach allows users to quickly navigate and find relevant information, from foundational toolkits and large-scale corpora to academic organizations and commercial services. The curation focuses on both specialized Chinese NLP resources and popular multi-language tools applicable to Chinese.

Quick Start & Requirements

• Installation: Primarily involves accessing linked GitHub repositories or official websites for specific tools and datasets.
• Prerequisites: Vary by tool, but commonly include Python, Java, C++, and sometimes specific deep learning frameworks (TensorFlow, PyTorch) or hardware (GPUs for advanced models).
• Resources: Links to official documentation, demos, and community channels are provided for most listed items.

Highlighted Details

• Extensive coverage of Chinese NLP toolkits, including popular ones like THULAC, BaiduLac, HanLP, and FastNLP, alongside multi-language tools like Stanford CoreNLP and spaCy.
• A rich collection of Chinese corpora, ranging from general text and news to specialized datasets for sentiment analysis, named entity recognition, and question answering.
• Listings of key Chinese NLP academic organizations, research labs, and industry players, alongside major NLP conferences and competitions.
• Inclusion of learning materials, such as books, course notes, and practical tutorials for deep learning and NLP tasks.

Maintenance & Community

The repository is a community-driven effort, with contributions from various academic institutions and individuals. Links to relevant organizations and conferences are provided, indicating active areas of research and development.

Licensing & Compatibility

Licenses vary significantly across the linked resources, ranging from permissive (MIT, Apache) to more restrictive licenses. Users must check the specific license for each tool or dataset to ensure compatibility with their intended use, especially for commercial applications.

Limitations & Caveats

As a curated list, the repository's content is dependent on the maintainers' ongoing updates. Some links may become outdated, and the rapidly evolving nature of NLP means new tools and datasets may not be immediately reflected. Users should verify the status and maintenance of individual projects.