What is word sense disambiguation good for?

TL;DR

This paper critically examines the role of word sense disambiguation in NLP, questioning its foundational assumptions and exploring its practical importance across various language understanding tasks.

Contribution

It challenges the notion that word senses are well-defined and essential for NLP applications, providing a theoretical critique and empirical investigation.

Findings

Word senses are context-dependent and purpose-specific.

Word sense ambiguity may not be a critical obstacle for many NLP tasks.

Theoretical underpinnings of word senses are lacking.

Abstract

Word sense disambiguation has developed as a sub-area of natural language processing, as if, like parsing, it was a well-defined task which was a pre-requisite to a wide range of language-understanding applications. First, I review earlier work which shows that a set of senses for a word is only ever defined relative to a particular human purpose, and that a view of word senses as part of the linguistic furniture lacks theoretical underpinnings. Then, I investigate whether and how word sense ambiguity is in fact a problem for different varieties of NLP application.