ChineseNER
A neural network model for Chinese named entity recognition
About
ChineseNER utilizes a bidirectional LSTM neural network combined with a CRF layer to perform named entity recognition on Chinese text. It processes sequences of Chinese characters, converting them into dense vector representations, and incorporates additional features for improved accuracy. This model is suitable for developers and researchers working on natural language processing tasks involving Chinese language data.
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- Last commit
- 8 years ago
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jingyuanzhang
Phd student, University of Chinese Academy of Sciences
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