Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/41612
Title: Learning predictive structures for Semantic Role Labeling of NomBank
Authors: Liu, C.
Ng, H.T. 
Issue Date: 2007
Source: Liu, C.,Ng, H.T. (2007). Learning predictive structures for Semantic Role Labeling of NomBank. ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics : 208-215. ScholarBank@NUS Repository.
Abstract: This paper presents a novel application of Alternating Structure Optimization (ASO) to the task of Semantic Role Labeling (SRL) of noun predicates in NomBank. ASO is a recently proposed linear multi-task learning algorithm, which extracts the common structures of multiple tasks to improve accuracy, via the use of auxiliary problems. In this paper, we explore a number of different auxiliary problems, and we are able to significantly improve the accuracy of the Nom- Bank SRL task using this approach. To our knowledge, our proposed approach achieves the highest accuracy published to date on the English NomBank SRL task. © 2007 Association for Computational Linguistics.
Source Title: ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics
URI: http://scholarbank.nus.edu.sg/handle/10635/41612
ISBN: 9781932432862
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

70
checked on Dec 9, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.