A Machine-Reading-Comprehension Method for Named Entity Recognition in Legal Documents

Author:

Zhang Xinrui,Luo Xudong

Publisher

Springer Nature Singapore

Reference24 articles.

1. Cui, Y., Che, W., Liu, T., Qin, B., Wang, S., Hu, G.: Revisiting pre-trained models for Chinese natural language processing. In: Findings of the Association for Computational Linguistics: EMNLP 2020, pp. 657–668 (2020)

2. Dai, Z., Wang, X., Ni, P., Li, Y., Li, G., Bai, X.: Named entity recognition using BERT BiLSTM CRF for Chinese electronic health records. In: 2019 12th International Congress on Image and Signal Processing, Biomedical Engineering and Informatics, pp. 1–5 (2019)

3. De Sanctis, F.M.: Artificial intelligence and innovation in Brazilian justice. Int. Ann. Criminol. 59(1), 1–10 (2021)

4. Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, vol. 1, pp. 4171–4186 (2019)

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Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. BERT-LBIA: A BERT-Based Late Bidirectional Interaction Attention Model for Legal Case Retrieval;Communications in Computer and Information Science;2023-11-26

2. Recent Progress on Named Entity Recognition Based on Pre-trained Language Models;2023 IEEE 35th International Conference on Tools with Artificial Intelligence (ICTAI);2023-11-06

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