Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/78343
Title: Semantic argument classification exploiting argument interdependence
Authors: Jiang, Z.P.
Li, J.
Ng, H.T. 
Issue Date: 2005
Source: Jiang, Z.P.,Li, J.,Ng, H.T. (2005). Semantic argument classification exploiting argument interdependence. IJCAI International Joint Conference on Artificial Intelligence : 1067-1072. ScholarBank@NUS Repository.
Abstract: This paper describes our research on automatic semantic argument classification, using the PropBank data [Kingsbury et al., 2002]. Previous research employed features that were based either on a full parse or shallow parse of a sentence. These features were mostly based on an individual semantic argument and the relation between the predicate and a semantic argument, but they did not capture the interdependence among all arguments of a predicate. In this paper, we propose the use of the neighboring semantic arguments of a predicate as additional features in determining the class of the current semantic argument. Our experimental results show significant improvement in the accuracy of semantic argument classification after exploiting argument interdependence. Argument classification accuracy on the standard Section 23 test set improves to 90.50%, representing a relative error reduction of 18%.
Source Title: IJCAI International Joint Conference on Artificial Intelligence
URI: http://scholarbank.nus.edu.sg/handle/10635/78343
ISSN: 10450823
Appears in Collections:Staff Publications

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

Page view(s)

37
checked on Feb 17, 2018

Google ScholarTM

Check


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