Paper: Using Lexical and Relational Similarity to Classify Semantic Relations

ACL ID E09-1071
Title Using Lexical and Relational Similarity to Classify Semantic Relations
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

Many methods are available for comput- ing semantic similarity between individ- ual words, but certain NLP tasks require the comparison of word pairs. This pa- per presents a kernel-based framework for application to relational reasoning tasks of this kind. The model presented here com- bines information about two distinct types of word pair similarity: lexical similarity and relational similarity. We present an efficient and flexible technique for imple- menting relational similarity and show the effectiveness of combining lexical and re- lational models by demonstrating state-of- the-art results on a compound noun inter- pretation task.