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Received:September 28, 2022 Revised:October 27, 2022
Received:September 28, 2022 Revised:October 27, 2022
中文摘要: 事件抽取是信息抽取领域的重点研究方向. 为了提升事件抽取效果, 解决通用事件抽取方法无法充分利用文本特征信息的问题, 提出了融合触发词特征的事件抽取方法. 通过构建远程触发词库, 为事件类型分类模型提供额外特征信息, 增强事件触发词的发掘能力, 再融合事件类型与触发词距离特征, 提升事件要素抽取模型的表示学习能力, 最后, 将事件类型分类模型与事件要素抽取模型串联, 提升事件抽取效果. 在DuEE数据集上进行实验, 与其他模型相比, 本模型提升了准确率、召回率、F1值, 证明了本模型的有效性.
中文关键词: 事件抽取|预训练模型|特征工程|深度学习|自然语言处理
Abstract:Event extraction is a key research area in information extraction. To improve the effect of event extraction and solve the problem that general event extraction methods cannot make full use of text feature information, an event extraction method fused with trigger word features is proposed. A remote trigger word database is constructed to provide additional feature information for the event classification model and enhance the discovery ability of event trigger words. Then, the event type and the distance features of trigger words are integrated to improve the representation and learning ability of the event element extraction model. Finally, the event classification model and the event element extraction model are connected in series to improve the event extraction effect. Experiments on the DuEE dataset demonstrate that compared with other models, this model improves the accuracy, recall, and F1 value, which proves the effectiveness of this model.
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王立才,李兴宇,黄杨琛,罗琪彬.融合触发词特征的事件抽取.计算机系统应用,2023,32(10):229-234
WANG Li-Cai,LI Xing-Yu,HUANG Yang-Chen,LUO Qi-Bin.Fusion of Trigger Word Features for Event Extraction.COMPUTER SYSTEMS APPLICATIONS,2023,32(10):229-234
王立才,李兴宇,黄杨琛,罗琪彬.融合触发词特征的事件抽取.计算机系统应用,2023,32(10):229-234
WANG Li-Cai,LI Xing-Yu,HUANG Yang-Chen,LUO Qi-Bin.Fusion of Trigger Word Features for Event Extraction.COMPUTER SYSTEMS APPLICATIONS,2023,32(10):229-234