@inproceedings{awale-jana-2022-enriching,
title = "Enriching {H}indi {W}ord{N}et Using Knowledge Graph Completion Approach",
author = "Awale, Sushil and
Jana, Abhik",
editor = "Ojha, Atul Kr. and
Ahmadi, Sina and
Liu, Chao-Hong and
McCrae, John P.",
booktitle = "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 = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.eurali-1.13",
pages = "81--85",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Enriching Hindi WordNet Using Knowledge Graph Completion Approach
%A Awale, Sushil
%A Jana, Abhik
%Y Ojha, Atul Kr.
%Y Ahmadi, Sina
%Y Liu, Chao-Hong
%Y McCrae, John P.
%S 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
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F awale-jana-2022-enriching
%X 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.
%U https://aclanthology.org/2022.eurali-1.13
%P 81-85
Markdown (Informal)
[Enriching Hindi WordNet Using Knowledge Graph Completion Approach](https://aclanthology.org/2022.eurali-1.13) (Awale & Jana, EURALI 2022)
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.