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Joint Extraction of Events and Entities within a Document Context

Authors :
Yang, Bishan
Mitchell, Tom
Source :
Proceedings of NAACL-HLT 2016, pages 289-299
Publication Year :
2016

Abstract

Events and entities are closely related; entities are often actors or participants in events and events without entities are uncommon. The interpretation of events and entities is highly contextually dependent. Existing work in information extraction typically models events separately from entities, and performs inference at the sentence level, ignoring the rest of the document. In this paper, we propose a novel approach that models the dependencies among variables of events, entities, and their relations, and performs joint inference of these variables across a document. The goal is to enable access to document-level contextual information and facilitate context-aware predictions. We demonstrate that our approach substantially outperforms the state-of-the-art methods for event extraction as well as a strong baseline for entity extraction.<br />Comment: 11 pages, 2 figures, published at NAACL 2016

Details

Database :
arXiv
Journal :
Proceedings of NAACL-HLT 2016, pages 289-299
Publication Type :
Report
Accession number :
edsarx.1609.03632
Document Type :
Working Paper