Paper: Joint Event Extraction via Structured Prediction with Global Features

ACL ID P13-1008
Title Joint Event Extraction via Structured Prediction with Global Features
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2013
Authors

Traditional approaches to the task of ACE event extraction usually rely on sequential pipelines with multiple stages, which suf- fer from error propagation since event trig- gers and arguments are predicted in isola- tion by independent local classifiers. By contrast, we propose a joint framework based on structured prediction which ex- tracts triggers and arguments together so that the local predictions can be mutu- ally improved. In addition, we propose to incorporate global features which ex- plicitly capture the dependencies of multi- ple triggers and arguments. Experimental results show that our joint approach with local features outperforms the pipelined baseline, and adding global features fur- ther improves the performance signifi- cantly. Our approach advances state-of- the-art se...