| Citation: | JING Xin, WANG Huafeng, LIU Qianfeng, et al. Named entity recognition in nuclear power field based on ELMo-GCN[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(12): 2556-2565. doi: 10.13700/j.bh.1001-5965.2021.0155(in Chinese)
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In the process of knowledge management in nuclear power, it's necessary to use named entity recognition to extract high-quality semantic entities for intelligent analysis and processing of text in nuclear power.On the basis of existing research, the recognition precision rate of the model for nested named entities is improved by enhancing the ability of the network rate to extract context information. The experimental results show that the proposed method improves the precision and recall rate significantly compared with the existing methods. Compared with the BiFlaG network, the precision rate is increased by 9.52%, the recall rate is increased by 8.51%, and the
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