Intelligent Identification Method of Legal Case Entity Based on BERT-BiLSTM-CRF

doi:10.13190/j.jbupt.2020-241

Journal of Beijing University of Posts and Telecommunications ›› 2021, Vol. 44 ›› Issue (4): 129-134.doi: 10.13190/j.jbupt.2020-241

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Intelligent Identification Method of Legal Case Entity Based on BERT-BiLSTM-CRF

GUO Zhi-xin, DENG Xiao-long

School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2020-11-30 Published:2021-07-13

Abstract

Abstract: In the past, artificial intelligence natural language processing related technologies often used static feature vector models in the application of intelligent legal systems, which had problems such as low algorithm efficiency and large accuracy deviations. To intelligently identify case entities in legal texts and improve case processing efficiency, the dynamic word vector model is studied, and a recognition method based on the bidirectional encoder representations from transformers model as the input layer is proposed. Based on the fusion of bi-directional long short-term memory and conditional random fields models, a high-precision method of intelligent identification of legal case entities is constructed. The performance of the model is verifiedthrough experiments.

Key words: natural language processing, intelligent legal affairs, bidirectional encoder representations from transformers model

CLC Number:

TP391.1

GUO Zhi-xin, DENG Xiao-long. Intelligent Identification Method of Legal Case Entity Based on BERT-BiLSTM-CRF[J]. Journal of Beijing University of Posts and Telecommunications, 2021, 44(4): 129-134.

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Intelligent Identification Method of Legal Case Entity Based on BERT-BiLSTM-CRF

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