Constructing information networks using one single model

Qi Li, Heng Ji, Yu Hong, Sujian Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a new framework that unifies the output of three information extraction (IE) tasks - entity mentions, relations and events as an information network representation, and extracts all of them using one single joint model based on structured prediction. This novel formulation allows different parts of the information network fully interact with each other. For example, many relations can now be considered as the resultant states of events. Our approach achieves substantial improvements over traditional pipelined approaches, and significantly advances state-of-the-art end-toend event argument extraction.

Original languageEnglish (US)
Title of host publicationEMNLP 2014 - 2014 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference
PublisherAssociation for Computational Linguistics (ACL)
Pages1846-1851
Number of pages6
ISBN (Electronic)9781937284961
StatePublished - Jan 1 2014
Externally publishedYes
Event2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014 - Doha, Qatar
Duration: Oct 25 2014Oct 29 2014

Publication series

NameEMNLP 2014 - 2014 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference

Conference

Conference2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014
CountryQatar
CityDoha
Period10/25/1410/29/14

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition
  • Information Systems

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