Fourteen linguistically-motivated numerical indicators are evaluated for their ability to categorize verbs as either {\it states} or {\it 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.