Duluth: Word Sense Discrimination in the Service of Lexicography

Abstract

This paper describes the Duluth systems that participated in Task 15 of SemEval 2015. The goal of the task was to automatically construct dictionary entries (via a series of three subtasks). Our systems participated in subtask 2, which involved automatically clustering the contexts in which a target word occurs into its different senses. Our results are consistent with previous word sense induction and discrimination findings, where it proves difficult to beat a baseline algorithm that assigns all instances of a target word to a single sense. However, our method of predicting the number of senses automatically fared quite well.