自动汇总
事件(粒子物理)
计算机科学
任务(项目管理)
鉴定(生物学)
信息抽取
情报检索
数据挖掘
自然语言处理
数据科学
工程类
物理
植物
系统工程
量子力学
生物
作者
Qi Liu,Zhaoqing Luan,Kunlong Wang,Ye Zou,Bing Liu,Yang Zhou
出处
期刊:Journal of physics
[IOP Publishing]
日期:2023-05-01
卷期号:2504 (1): 012008-012008
标识
DOI:10.1088/1742-6596/2504/1/012008
摘要
Abstract Event extraction aims to detect occurrences of specified types and extract corresponding event arguments from unstructured data input, which is an integral part of information extraction [1]. Many downstream tasks, such as text summarization, causal relationship identification, and event reasoning, make extensive use of event extraction. However, most of the existing research on event extraction remains at the sentence level. Document-level event extraction is still under exploration and lacks relevant review. Focusing on the task of document-level event extraction, this survey first divides the existing technologies into three categories and introduces the most representative models; Then, we list some commonly used datasets for document-level event extraction with their usage messages; Finally, we analyse the current research gaps of document-level event extraction and future research trends.
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