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Named Entity Recognition for Chinese Construction Documents

In: Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate

Author

Listed:
  • Xing Su

    (Zhejiang University)

  • Zirui Hong

    (Zhejiang University)

  • Qiqi Zhang

    (Zhejiang University)

  • Cong Xue

    (Zhejiang University)

  • Xu Li

    (Zhejiang University)

Abstract

Named Entity Recognition plays a critical role in many Natural Language Processing tasks such as information extraction, document classification and knowledge management. A construction document usually contains critical named entities and an effective NER method can provide a solid foundation for NLP applications, leading to a better efficiency of construction management. This paper focuses on NER for Chinese construction documents. The background and current challenges were introduced. An NER framework were proposed including the system structure, the annotation strategy and the model training approach. The result of a pilot test that implements the framework is presented and future research directions for improvements were discussed by the end of the paper.

Suggested Citation

  • Xing Su & Zirui Hong & Qiqi Zhang & Cong Xue & Xu Li, 2021. "Named Entity Recognition for Chinese Construction Documents," Springer Books, in: Gui Ye & Hongping Yuan & Jian Zuo (ed.), Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate, pages 839-850, Springer.
    • Handle: RePEc:spr:sprchp:978-981-15-8892-1_60
    DOI: 10.1007/978-981-15-8892-1_60
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