Paper: Novel Word-sense Identification

ACL ID C14-1154
Title Novel Word-sense Identification
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014

Automatic lexical acquisition has been an active area of research in computational linguistics for over two decades, but the automatic identification of new word-senses has received attention only very recently. Previous work on this topic has been limited by the availability of appropriate evaluation resources. In this paper we present the largest corpus-based dataset of diachronic sense differences to date, which we believe will encourage further work in this area. We then describe several extensions to a state-of-the-art topic modelling approach for identifying new word-senses. This adapted method shows superior performance on our dataset of two different corpus pairs to that of the original method for both: (a) types having taken on a novel sense over time; and (b) the token instances ...