Automatic Tripartite Classification of Intransitive Verbs

In this paper, we introduce a tripartite scheme for the classification of intransitive verbs for Hindi and claim it to be a more suitable model of classification than the classical binary unaccusative/unergative classification. We develop a multi-class SVM classifier based model for automatic classification of intransitive verbs into proposed tripartite classes. We rank the unaccusative diagnostic tests for Hindi based on their authenticity in attesting an intransitive verb under unaccussative class. We show that the use of the ranking score in the feature of the classifier improves the efficiency of the classification model even with a small amount of data. The empirical result illustrates the fact that judicious use of linguistic knowledge builds a better classification model than the one that is purely statistical.