Enriching Hindi WordNet Using Knowledge Graph Completion Approach

Sushil Awale, Abhik Jana


Abstract
Even though the use of WordNet in the Natural Language Processing domain is unquestionable, creating and maintaining WordNet is a cumbersome job and it is even difficult for low resource languages like Hindi. In this study, we aim to enrich the Hindi WordNet automatically by using state-of-the-art knowledge graph completion (KGC) approaches. We pose the automatic Hindi WordNet enrichment problem as a knowledge graph completion task and therefore we modify the WordNet structure to make it appropriate for applying KGC approaches. Second, we attempt five KGC approaches of three different genres and compare the performances for the task. Our study shows that ConvE is the best KGC methodology for this specific task compared to other KGC approaches.
Anthology ID:
2022.eurali-1.13
Volume:
Proceedings of the Workshop on Resources and Technologies for Indigenous, Endangered and Lesser-resourced Languages in Eurasia within the 13th Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Editors:
Atul Kr. Ojha, Sina Ahmadi, Chao-Hong Liu, John P. McCrae
Venue:
EURALI
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
81–85
Language:
URL:
https://aclanthology.org/2022.eurali-1.13
DOI:
Bibkey:
Cite (ACL):
Sushil Awale and Abhik Jana. 2022. Enriching Hindi WordNet Using Knowledge Graph Completion Approach. In Proceedings of the Workshop on Resources and Technologies for Indigenous, Endangered and Lesser-resourced Languages in Eurasia within the 13th Language Resources and Evaluation Conference, pages 81–85, Marseille, France. European Language Resources Association.
Cite (Informal):
Enriching Hindi WordNet Using Knowledge Graph Completion Approach (Awale & Jana, EURALI 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.eurali-1.13.pdf
Code
 uhh-lt/hindi-wordnet-extension