Assessing wordnets with WordNet embeddings

Ruben Branco, João Rodrigues, Chakaveh Saedi, António Branco

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Abstract

An effective conversion method was proposed in the literature to obtain a lexical semantic space from a lexical semantic graph, thus permitting to obtain WordNet embeddings from WordNets. In this paper, we propose the exploitation of this conversion methodology as the basis for the comparative assessment of WordNets: given two WordNets, their relative quality in terms of capturing the lexical semantics of a given language, can be assessed by (i) converting each WordNet into the corresponding semantic space (i.e. into WordNet embeddings), (ii) evaluating the resulting WordNet embeddings under the typical semantic similarity prediction task used to evaluate word embeddings in general; and (iii) comparing the performance in that task of the two word embeddings, extracted from the two WordNets. A better performance in that evaluation task results from the word embeddings that are better at capturing the semantic similarity of words, which, in turn, result from the WordNet that is of higher quality at capturing the semantics of words.

Original languageEnglish
Title of host publicationProceedings of the 10th Global WordNet Conference
EditorsChristiane Fellbaum, Piek Vossen, Ewa Rudnicka, Marek Maziarz, Maciej Piasecki
PublisherGlobal Wordnet Association
Pages253-259
Number of pages7
ISBN (Electronic)9788374931083
Publication statusPublished - 2019
Event10th Global WordNet Conference, GWC 2019 - Wroclaw, Poland
Duration: 23 Jul 201927 Jul 2019

Publication series

NameProceedings of the 10th Global WordNet Conference

Conference

Conference10th Global WordNet Conference, GWC 2019
CountryPoland
CityWroclaw
Period23/07/1927/07/19

Bibliographical note

Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

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