Diarmuid Ó Séaghdha
Using lexical and relational similarity to classify semantic relations
Diarmuid Ó Séaghdha and Ann Copestake, EACL 2009
Many methods are available for computing semantic similarity between individual words, but certain NLP tasks require the comparison of word pairs. This paper presents a kernel-based framework for application to relational reasoning tasks of this kind. The model presented here combines information about two distinct types of word pair similarity: lexical similarity and relational similarity. We present an efficient and flexible technique for implementing relational similarity and show the effectiveness of combining lexical and relational models by demonstrating state-of-the-art results on a compound noun interpretation task.
@InProceedings{OSeaghdha:Copestake:09, author = {Diarmuid {\'O S\'eaghdha} and Ann Copestake}, title = {Using lexical and relational similarity to classify semantic relations}, booktitle = {Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (EACL-09)}, year = 2009, address = {Athens,Greece} }