Named Entity Recognition for Chinese Construction Documents

Xing Su (), Zirui Hong, Qiqi Zhang, Cong Xue and Xu Li
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Xing Su: Zhejiang University
Zirui Hong: Zhejiang University
Qiqi Zhang: Zhejiang University
Cong Xue: Zhejiang University
Xu Li: Zhejiang University

A chapter in Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate, 2021, pp 839-850 from Springer

Abstract: 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.

Keywords: NER; NLP; Chinese; Construction document; Deep-learning (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-15-8892-1_60

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DOI: 10.1007/978-981-15-8892-1_60

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