Element relational graph-augmented multi-granularity contextualized encoding for document-level event role filler extraction  

作　　者：Enchang ZHU Zhengtao YU Yuxin HUANG Shengxiang GAO Yantuan XIAN 

机构地区：[1]Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China [2]Yunnan Key Laboratory of Artificial Intelligence,Kunming University of Science and Technology,Kunming 650500,China

出　　处：《Frontiers of Computer Science》2025年第2期137-138,共2页计算机科学前沿(英文版)

基　　金：supported by the National Natural Science Foundation of China(Grant Nos.U21B2027,U23A20388,62266028);the Yunnan Provincial Major Science and Technology Special Plan Projects(202302AD080003,202202AD080003,202303AP140008);the Yunnan Fundamental Research Projects(202301AS070047);the Kunming University of Science and Technology’s”Double First-rate”Construction Joint Project(202201BE070001-021).

摘　　要：1 Introduction Document-level Role Filler Extraction aims to identify those spans of text that denote the role fillers for each event described in the document[1].Despite achieving certain accomplishments,existing methods are still not effective due to the following two issues:(1)there are difficulties in contextual modeling of long text,which requires modeling and understanding coherence and connections across sentences and paragraphs;(2)there usually ignore the explicit dependency relationships between event elements displayed in long text.To this end,we propose a novel graph-augmented approach for document-level event role filler extraction,named element relational graph-augmented multi-granularity contextualized encoder(ERGM),whose main idea is to effectively enhance the model's capabilities in capturing deep semantic information of events in long texts and modeling dependency relationships among event elements by incorporating the Event elements relational graph.Specifically,this method first constructs the structural graph by extracting elements from the source document.

关 键 词：CONTEXTUAL SPITE semantic 

分 类 号：H31[语言文字—英语]