Exploring the Enrichment of Basque WordNet with a Sentiment Lexicon

Itziar Gonzalez-Dios, Jon Alkorta


Abstract
Wordnets are lexical databases where the semantic relations of words and concepts are established. These resources are useful for manyNLP tasks, such as automatic text classification, word-sense disambiguation or machine translation. In comparison with other wordnets,the Basque version is smaller and some PoS are underrepresented or missing e.g. adjectives and adverbs. In this work, we explore anovel approach to enrich the Basque WordNet, focusing on the adjectives. We want to prove the use and and effectiveness of sentimentlexicons to enrich the resource without the need of starting from scratch. Using as complementary resources, one dictionary and thesentiment valences of the words, we check if the word of the lexicon matches with the meaning of the synset, and if it matches we addthe word as variant to the Basque WordNet. Following this methodology, we describe the most frequent adjectives with positive andnegative valence, the matches and the possible solutions for the non-matches.
Anthology ID:
2020.mmw-1.4
Volume:
Proceedings of the LREC 2020 Workshop on Multimodal Wordnets (MMW2020)
Month:
May
Year:
2020
Address:
Marseille, France
Venues:
LREC | MMW | WS
SIG:
Publisher:
The European Language Resources Association (ELRA)
Note:
Pages:
20–24
Language:
English
URL:
https://www.aclweb.org/anthology/2020.mmw-1.4
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.mmw-1.4.pdf