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Five-Stroke Based CNN-BiRNN-CRF Network for Chinese Named Entity Recognition

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Natural Language Processing and Chinese Computing (NLPCC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11108))

Abstract

Identifying entity boundaries and eliminating entity ambiguity are two major challenges faced by Chinese named entity recognition researches. This paper proposes a five-stroke based CNN-BiRNN-CRF network for Chinese named entity recognition. In terms of input embeddings, we apply five-stroke input method to obtain stroke-level representations, which are concatenated with pre-trained character embeddings, in order to explore the morphological and semantic information of characters. Moreover, the convolutional neural network is used to extract n-gram features, without involving hand-crafted features or domain-specific knowledge. The proposed model is evaluated and compared with the state-of-the-art results on the third SIGHAN bakeoff corpora. The experimental results show that our model achieves 91.67% and 90.68% F1-score on MSRA corpus and CityU corpus separately.

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Notes

  1. 1.

    https://en.wikipedia.org/wiki/Wubi_method.

  2. 2.

    https://github.com/yanhuacuo/98wubi-tables.

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Acknowledgement

This research work has been funded by the National Natural Science Foundation of China (Grant No. 61772337, U1736207 and 61472248), the SJTU-Shanghai Songheng Content Analysis Joint Lab, and program of Shanghai Technology Research Leader (Grant No. 16XD1424400).

Author information

Authors and Affiliations

  1. School of Electric Information and Electronic Engineering, Shanghai Jiaotong University, Shanghai, China

    Fan Yang, Jianhu Zhang, Gongshen Liu & Jie Zhou

  2. SJTU-Shanghai Songheng Content Analysis Joint Lab, Shanghai, China

    Cheng Zhou & Huanrong Sun

Authors
  1. Fan Yang
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  2. Jianhu Zhang
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  3. Gongshen Liu
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  4. Jie Zhou
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  5. Cheng Zhou
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  6. Huanrong Sun
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Corresponding author

Correspondence to Gongshen Liu .

Editor information

Editors and Affiliations

  1. Soochow University, Suzhou, China

    Min Zhang

  2. The University of Texas at Dallas, Richardson, Texas, USA

    Vincent Ng

  3. Peking University, Beijing, China

    Dongyan Zhao

  4. Peking University, Beijing, China

    Sujian Li

  5. Zhengzhou University, Zhengzhou, China

    Hongying Zan

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Yang, F., Zhang, J., Liu, G., Zhou, J., Zhou, C., Sun, H. (2018). Five-Stroke Based CNN-BiRNN-CRF Network for Chinese Named Entity Recognition. In: Zhang, M., Ng, V., Zhao, D., Li, S., Zan, H. (eds) Natural Language Processing and Chinese Computing. NLPCC 2018. Lecture Notes in Computer Science(), vol 11108. Springer, Cham. https://doi.org/10.1007/978-3-319-99495-6_16

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  • DOI: https://doi.org/10.1007/978-3-319-99495-6_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99494-9

  • Online ISBN: 978-3-319-99495-6

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