计算机工程与应用2025，Vol.61Issue(10)：111-119,9.DOI:10.3778/j.issn.1002-8331.2402-0185
结合二维增强融合机制的事件论元抽取方法
Event Argument Extraction with Two-Dimensional Enhanced Fusion Mechanism
摘要
Abstract
Addressing the lack of interaction between trigger and arguments,and the lack of interaction within channels in existing studies of event argument extraction,this paper proposes a two-dimensional enhanced fusion mechanism for event argument extraction(W2-ARG)that incorporates a 2D enhanced fusion method.It inserts identifiers on both sides of a trigger word in a sentence,which encodes information about the event type.In the learning process,it is effective to enhance the interaction between trigger and argument,and encode the trigger separately to highlight its information in the sentence.The event argument extraction is implemented as a two-dimensional representation of label prediction.It has the advantage to capture semantic interactions of words at different distances through dilated convolution.Subsequently,a channel attention module is applied to enhance the interactions within the channel to strengthen the information transfer within the channel.Finally,the Laplace operator is utilized to highlight the positional features of event arguments in the semantic space to improve the performance.The proposed model is experimented on the ACE05-EN and ERE-EN datasets.Experimental results show clear performance improvement of the proposed model compared with other event argument extraction methods.关键词
事件论元抽取/句子平面化表示/通道注意力/拉普拉斯算子/BERTKey words
event argument extraction/sentence planarization representation/channel attention/Laplace operator/BERT分类
信息技术与安全科学引用本文复制引用
王潞翔,陈艳平,黄辉,黄瑞章,秦永彬..结合二维增强融合机制的事件论元抽取方法[J].计算机工程与应用,2025,61(10):111-119,9.基金项目
国家重点研发计划(2023YFC3304500) （2023YFC3304500）
国家自然科学基金(62166007). （62166007）
