Event extraction enhanced by fusing trigger feature

Xingyu Li; Licai Wang; Yangchen Huang; Qibin Luo; Tianfeng Du

doi:10.1117/12.2660155

3 February 2023 Event extraction enhanced by fusing trigger feature

Xingyu Li, Licai Wang, Yangchen Huang, Qibin Luo, Tianfeng Du

Proceedings Volume 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022); 1251110 (2023) https://doi.org/10.1117/12.2660155
Event: Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 2022, Hulun Buir, China

Abstract

Event extraction is a key research direction in the field of information extraction. In order to improve the effect of event extraction and solve the problem that the general event extraction method cannot make full use of the text feature information, an event extraction method integrating trigger word features is proposed. By building a remote trigger thesaurus, we can provide additional feature information for the event type classification model, enhance the ability of discovering event trigger words. Then the event arguments extraction model integrates the event type and trigger distance features to improve the representation learning ability. Finally, connecting the event type classification model and the event arguments extraction model in series to complete event extraction. Experiments are carried out on the DuEE dataset and the result shows that our model has more outstanding performance than other models.

Citation Download Citation

Xingyu Li, Licai Wang, Yangchen Huang, Qibin Luo, and Tianfeng Du "Event extraction enhanced by fusing trigger feature", Proc. SPIE 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 1251110 (3 February 2023); https://doi.org/10.1117/12.2660155

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