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A comparative study of Chinese named entity recognition with different segment representations

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Abstract

Named entity recognition (NER) is a fundamental but crucial task in the field of natural language processing and has been widely studied. Nevertheless, little attention has been given to the segment representation (SR) schemes used to map multi-token entities into categories in Chinese NER. To address this issue, in this paper, we explore and compare the impact of using different SR schemes on Chinese NER. Our experiments are conducted on four benchmark Chinese NER datasets extended with labels to include seven well-known SR schemes: IO, IOB2, IOE2, IOBES, BI, IE, and BIES. Moreover, all seven SR schemes are investigated via two sets of classifiers: machine learning-based and neural network-based classifiers. The experimental results demonstrate that the proper selection of the best SR scheme is a complicated problem that depends on various factors, such as corpus size, corpus distribution, and the chosen classifier. We also provide a comparative analysis of the time consumption of each classifier in different SR schemes and discuss the impacts of using different SR schemes on NER in Chinese and other languages.

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Acknowledgments

This work is supported by the Zhejiang Public Welfare Technology Application Research Project of China (grant: LGN21F020003), National Natural Science Foundation of China (grant: 12001489), the key project of Humanities and Social Sciences in Colleges and Universities of Zhejiang Province (No 2021GH017), Humanities and Social Sciences Project of the Ministry of Education of China (No 21YJA870011) and Zhejiang Youth Project of Zhejiang Philosophy and Social Sciences Planning (No 22ZJQN45YB).

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Authors and Affiliations

  1. Laboratory of Artificial Intelligence, School of Science, Zhejiang University of Science and Technology, Hangzhou, 310023, Zhejiang, China

    Jun Pan & Chaohua Zhang

  2. School of Electronic and Information Engineering, Taizhou University, Taizhou, 318000, Zhejiang, China

    Haijun Wang

  3. Department of Computer Science and Engineering, Shaoxing University, Shaoxing, 312000, Zhejiang, China

    Zongda Wu

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  1. Jun Pan
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Correspondence to Zongda Wu.

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Pan, J., Zhang, C., Wang, H. et al. A comparative study of Chinese named entity recognition with different segment representations. Appl Intell 52, 12457–12469 (2022). https://doi.org/10.1007/s10489-022-03274-0

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