A survey of document-level relation extraction

Jiaqi Wang; Yahui Li; Jing Huang; Wenbin Zhao

doi:10.1117/12.2641047

2 December 2022 A survey of document-level relation extraction

Jiaqi Wang, Yahui Li, Jing Huang, Wenbin Zhao

Proceedings Volume 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022); 122881S (2022) https://doi.org/10.1117/12.2641047
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 2022, Zhuhai, China

Abstract

Relation extraction is the core mission and a great significant part of natural language processing. This paper briefly expound the development of relation extraction and introduces the commonly used document-level relation extraction datasets and evaluation indexes of model effects. According to the different representation of entity by model, documentlevel relation extraction can be divided into sequential method and graph method. Besides, we conduct contrastive analysis concerning different relation extraction models, and compared the effects of various relation extraction models. Finally, we summarize the key research contents of document-level relation extraction in the future and forecast the development trend.

Citation Download Citation

Jiaqi Wang, Yahui Li, Jing Huang, and Wenbin Zhao "A survey of document-level relation extraction", Proc. SPIE 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 122881S (2 December 2022); https://doi.org/10.1117/12.2641047

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