Joint event extraction based on hierarchical event schemas from framenet


Event extraction is useful for many practical applications, such as news summarization and information retrieval. However, the popular automatic context extraction (ACE) event extraction program only defines very limited and coarse event schemas, which may not be suitable for practical applications. FrameNet is a linguistic corpus that defines complete semantic frames and frame-to-frame relations. As frames in FrameNet share highly similar structures with event schemas in ACE and many frames actually express events, we propose to redefine the event schemas based on FrameNet. Specifically, we extract frames expressing event information from FrameNet and leverage the frame-to-frame relations to build a hierarchy of event schemas that are more fine-grained and have much wider coverage than ACE. Based on the new event schemas, we propose a joint event extraction approach that leverages the hierarchical structure of event schemas and frame-to-frame relations in FrameNet. The extensive experiments have verified the advantages of our hierarchical event schemas and the effectiveness of our event extraction model. We further apply the results of our event extraction model on news summarization. The results show that the summarization approach based on our event extraction model achieves significant better performance than several state-of-the-art summarization approaches, which also demonstrates that the hierarchical event schemas and event extraction model are promising to be used in the practical applications.

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Divisions: College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > Aston Institute of Materials Research (AIMR)
College of Engineering & Physical Sciences > Energy and Bioproducts Research Institute (EBRI)
Funding Information: This work was supported in part by the National Key Research and Development Program of China under Grant 2016YFB1000902, and in part by the National Natural Science Foundation of China under Grant U1836206, Grant 61572469, Grant 91646120, Grant 61772501,
Additional Information: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This is an open access article
Uncontrolled Keywords: Event extraction,event schema definition,information extraction,joint inference,Computer Science(all),Materials Science(all),Engineering(all)
Publication ISSN: 2169-3536
Last Modified: 25 Mar 2024 08:31
Date Deposited: 25 Mar 2019 12:33
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2019-03-07
Published Online Date: 2019-02-18
Accepted Date: 2019-02-10
Authors: Li, Wei (ORCID Profile 0000-0003-4036-467X)
Cheng, Dezhi
He, Lei
Wang, Yuanzhuo
Jin, Xiaolong



Version: Published Version

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