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In this paper, we discuss the enrichment of a manually developed resource ofTelugu lexicon, OntoSenseNet. OntoSenseNet is a ontological sense annotatedlexicon that marks each verb of Telugu with a primary and a secondary sense.The area of research is relatively recent but has a large scope of development.We provide an introductory work to enrich the OntoSenseNet to promote furtherresearch in Telugu. Classifiers are adopted to learn the sense relevantfeatures of the words in the resource and also to automate the tagging ofsense-types for verbs. We perform a comparative analysis of differentclassifiers applied on OntoSenseNet. The results of the experiment prove thatautomated enrichment of the resource is effective using SVM classifiers andAdaboost ensemble.

Towards Automation of Sense-type Identification of Verbs in OntoSenseNet(Telugu)