Recognizing Chinese judicial named entity using BiLSTM-CRF

  title={Recognizing Chinese judicial named entity using BiLSTM-CRF},
  author={Pin Tang and Pinli Yang and Yuang Shi and Yi Zhou and Feng Lin and Yan Wang},
  journal={Journal of Physics: Conference Series},
Named entity recognition (NER) plays an essential role in natural language processing systems. Judicial NER is a fundamental component of judicial information retrieval, entity relation extraction, and knowledge map building. However, Chinese judicial NER remains to be more challenging due to the characteristics of Chinese and high accuracy requirements in the judicial filed. Thus, in this paper, we propose a deep learning-based method named BiLSTM-CRF which consists of bi-directional long… 

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Proceedings of the 4 th International Conference on Data Mining in Bioinformatics ( Citeseer )

  • 2004