Know Your Graph. State-of-the-Art Knowledge-Based WSD

Alexander Popov, Kiril Simov, Petya Osenova


Abstract
This paper introduces several improvements over the current state of the art in knowledge-based word sense disambiguation. Those innovations are the result of modifying and enriching a knowledge base created originally on the basis of WordNet. They reflect several separate but connected strategies: manipulating the shape and the content of the knowledge base, assigning weights over the relations in the knowledge base, and the addition of new relations to it. The main contribution of the paper is to demonstrate that the previously proposed knowledge bases organize linguistic and world knowledge suboptimally for the task of word sense disambiguation. In doing so, the paper also establishes a new state of the art for knowledge-based approaches. Its best models are competitive in the broader context of supervised systems as well.
Anthology ID:
R19-1110
Volume:
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
Month:
September
Year:
2019
Address:
Varna, Bulgaria
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
949–958
Language:
URL:
https://www.aclweb.org/anthology/R19-1110
DOI:
10.26615/978-954-452-056-4_110
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PDF:
http://aclanthology.lst.uni-saarland.de/R19-1110.pdf