Semantic classification with WordNet kernels

Authors:
Diarmuid Ó Séaghdha
Affiliations:
University of Cambridge, United Kingdom
Venue:
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Year:
2009

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Abstract

This paper presents methods for performing graph-based semantic classification using kernel functions defined on the WordNet lexical hierarchy. These functions are evaluated on the SemEval Task 4 relation classification dataset and their performance is shown to be competitive with that of more complex systems. A number of possible future developments are suggested to illustrate the flexibility of the approach.