Learning Methods for Combining Linguistic Indicators to Classify Verbs

Abstract

Fourteen linguistically-motivated numerical indicators are evaluated for their ability to categorize verbs as either states or events. The values for each indicator are computed automatically across a corpus of text. To improve classification performance, machine learning techniques are employed to combine multiple indicators. Three machine learning methods are compared for this task: decision tree induction, a genetic algorithm, and log-linear regression.

7 pages, Latex, in the Proceedings of the Second Conference on Empirical Methods in Natural Language Processing, Providence, Rhode Island, 1997