Semi-automatic WordNet Linking using Word Embeddings

Kevin Patel, Diptesh Kanojia, Pushpak Bhattacharyya


Abstract
Wordnets are rich lexico-semantic resources. Linked wordnets are extensions of wordnets, which link similar concepts in wordnets of different languages. Such resources are extremely useful in many Natural Language Processing (NLP) applications, primarily those based on knowledge-based approaches. In such approaches, these resources are considered as gold standard/oracle. Thus, it is crucial that these resources hold correct information. Thereby, they are created by human experts. However, manual maintenance of such resources is a tedious and costly affair. Thus techniques that can aid the experts are desirable. In this paper, we propose an approach to link wordnets. Given a synset of the source language, the approach returns a ranked list of potential candidate synsets in the target language from which the human expert can choose the correct one(s). Our technique is able to retrieve a winner synset in the top 10 ranked list for 60% of all synsets and 70% of noun synsets.
Anthology ID:
2018.gwc-1.31
Volume:
Proceedings of the 9th Global Wordnet Conference
Month:
January
Year:
2018
Address:
Nanyang Technological University (NTU), Singapore
Editors:
Francis Bond, Piek Vossen, Christiane Fellbaum
Venue:
GWC
SIG:
SIGLEX
Publisher:
Global Wordnet Association
Note:
Pages:
266–271
Language:
URL:
https://aclanthology.org/2018.gwc-1.31
DOI:
Bibkey:
Cite (ACL):
Kevin Patel, Diptesh Kanojia, and Pushpak Bhattacharyya. 2018. Semi-automatic WordNet Linking using Word Embeddings. In Proceedings of the 9th Global Wordnet Conference, pages 266–271, Nanyang Technological University (NTU), Singapore. Global Wordnet Association.
Cite (Informal):
Semi-automatic WordNet Linking using Word Embeddings (Patel et al., GWC 2018)
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PDF:
https://aclanthology.org/2018.gwc-1.31.pdf