Merging Verb Senses of Hindi WordNet using Word Embeddings
نویسندگان
چکیده
In this paper, we present an approach for merging fine-grained verb senses of Hindi WordNet. Senses are merged based on gloss similarity score. We explore the use of word embeddings for gloss similarity computation and compare with various WordNet based gloss similarity measures. Our results indicate that word embeddings show significant improvement over WordNet based measures. Consequently, we observe an increase in accuracy on merging fine-grained senses. Gold standard data constructed for our experiments is made available.
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