buppt/ChineseNER

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1463 stars · 388 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A simple Chinese named entity recognition (NER) implementation using BiLSTM+CRF in both TensorFlow and PyTorch. It includes training scripts and three open Chinese datasets (Boson, People's Daily 1998, MSRA) for entity extraction of names, locations, and organizations.

Use cases

• train a Chinese NER model with BiLSTM+CRF
• extract entities like names, places, and organizations from Chinese text
• learn how sequence labeling and CRF work with a minimal example
• run named entity recognition on a text file and write results to another file
• experiment with pretrained word embeddings for Chinese NER

When to choose

• you want a minimal, easy-to-read BiLSTM+CRF NER implementation for Chinese
• you need a learning resource or baseline for Chinese entity extraction
• you want bundled open Chinese NER datasets to start training immediately

When to avoid

• you need production-grade accuracy or actively maintained code (last updated 2020, old TensorFlow 1.7/PyTorch 0.4, Python 2.7)
• you need multilingual NER or transformer-based models
• you need fast training - the PyTorch version has no batching and is very slow

Facets

library · maturity maintenance

nlp machine-learning deep-learning machine-learning localization python windows named-entity-recognition bilstm-crf chinese-ner tensorflow pytorch entity-extraction natural-language-processing linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="buppt/ChineseNER")