Automated Learning Applied to Functional Argument Identification

Abstract

This paper reports experiments on applying machine learning to identifying functional arguments of verbs such as logical subject. In particular, it is shown that using decision trees for functional arguments identification is beneficial. The paper also argues that linguistically-motivated features gathered from a large corpus can capture functional information.