事件抽取方法综述:深度学习与预训练对比分析

Survey on Event Extraction Methods:Comparative Analysis of Deep Learning and Pre-training

事件抽取是伴随着信息技术的发展而诞生的。随着人们对从繁多的日常信息中抽取出有用信息的需求日益增强,事件抽取的研究发展也越发受重视。首先,介绍了事件抽取的发展历程,理清了事件抽取的发展脉络;其次,介绍了事件抽取的2种范式,并对管道型抽取和联合型抽取范式进行了对比分析;再次,围绕事件抽取的层级,分别从句子级事件抽取和篇章级事件抽取2个层面对近年来事件抽取的发展进行了梳理;然后,从传统型事件抽取方法、基于深度学习的事件抽取方法,以及基于预训练模型的事件抽取方法3个方面对事件抽取方法进行了对比分析;最后,介绍了事件抽取的典型应用场景,并根据事件抽取的发展现状,对未来事件抽取前沿发展进行了展望。

Event extraction is born along with the development of information technology.As people’s demand for extracting useful information from a wide variety of daily information is increasing,the research and development of event extraction has attracted more and more attention.This paper first introduces the development process of event extraction,clarifies the development context of event extraction,and then introduces two paradigms of event extractionand a comparative analysis of pipeline and fe-derated extraction paradigms is presented.Secondly,according to the level of event extraction,the development of event extraction in recent years is described from sentence level event extraction and text level event extraction.Then,the event extraction me-thods are compared and analyzed from three aspects:traditional event extraction methods,deep learning based event extraction methods,and Pre-training model-based event extraction methods.Finally,some typical application scenarios of event extraction are introduced,and the future development of event extraction topics is prospected according to the development status of event extraction.