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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 12

Chinese named entity recognition method based on Biaffine mechanism and lexical enhancement

Zhang Runmeia,b
Wang Mingxia
Chen Zhongb
a. School of Electronic & Information Engineering, b. School of Mechanical & Electrical Engineering, Anhui Jianzhu University, Hefei 230601, China
DOI: 10.19734/j.issn.1001-3695.2025.05.0152

Abstract

To address the challenges of fuzzy entity boundaries, complex structures, and scarce domain-specific data in Chinese Named Entity Recognition (NER) , we propose WLASC, a Chinese NER model based on a biaffine mechanism and lexical enhancement. In the encoding layer, the model incorporates a dynamic biaffine module and a multi-level lexical enhancement module. By introducing relative position encoding and biaffine transformation, the model strengthens contextual modeling capabilities, effectively resolving fuzzy entity boundaries. Simultaneously, it leverages multi-level lexical information and a multi-head attention mechanism to weight and fuse features of different granularities, improving nested entity recognition accuracy while reducing reliance on annotated data. Additionally, the model employs a bidirectional gated recurrent neural network to fuse extracted features, further enhancing its expressive power. Experimental results on the aviation flight safety domain dataset CANER and public datasets (Weibo, Resume) demonstrate that the improved algorithm achieves maximum F1-score improvements of 9.77%, 6.97%, and 1.38%, respectively, with minimum improvements of 2.72%, 1.27%, and 0.31%. Tests on the CANER dataset confirm that the model effectively handles structurally complex entities and domain-specific terminology in specialized Chinese domains. Experiments on public datasets further indicate that the model exhibits strong generalization capabilities.

Foundation Support

国家自然科学基金一般项目(52378001)
基于知识图谱构建无人机安全知识库(FZ2021KF10)
安徽省高校自然科学项目(2024AH050234)
大学储备基金项目(2022XMK03)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.05.0152
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 12

Publish History

[2025-08-18] Accepted Paper

Cite This Article

张润梅, 王明曦, 陈中. 基于Biaffine机制和词汇增强的中文命名实体识别方法 [J]. 计算机应用研究, 2025, 42 (12). (2025-08-21). https://doi.org/10.19734/j.issn.1001-3695.2025.05.0152. (Zhang Runmei, Wang Mingxi, Chen Zhong. Chinese named entity recognition method based on Biaffine mechanism and lexical enhancement [J]. Application Research of Computers, 2025, 42 (12). (2025-08-21). https://doi.org/10.19734/j.issn.1001-3695.2025.05.0152. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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