Merging Verb Senses of Hindi WordNet using Word Embeddings.
- Sudha Bhingardive,
- ,
- Dhirendra Singh,
- Pushpak Bhattacharyya
- Indian Institute of Technology Bombay
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review
Open access
Publication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOriginal language
Undefined/UnknownPages from-to (Number of pages)
Pages 344-352Publication milestones
- Published - 2014
Publication status
Published - 2014
Host publication title
Proceedings of the 11th International Conference on Natural Language ProcessingAbstract
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.
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.