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        <title>Assessing Wordnets with WordNet Embeddings</title>
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            <title>Proceedings of the 10th Global Wordnet Conference</title>
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            <namePart type="family">Vossen</namePart>
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            <namePart type="given">Christiane</namePart>
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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.</abstract>
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%0 Conference Proceedings
%T Assessing Wordnets with WordNet Embeddings
%A Branco, Ruben
%A Rodrigues, João
%A Saedi, Chakaveh
%A Branco, António
%Y Vossen, Piek
%Y Fellbaum, Christiane
%S Proceedings of the 10th Global Wordnet Conference
%D 2019
%8 July
%I Global Wordnet Association
%C Wroclaw, Poland
%F branco-etal-2019-assessing
%X 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.
%U https://aclanthology.org/2019.gwc-1.32
%P 253-259

Markdown (Informal)

[Assessing Wordnets with WordNet Embeddings](https://aclanthology.org/2019.gwc-1.32) (Branco et al., GWC 2019)

• Assessing Wordnets with WordNet Embeddings (Branco et al., GWC 2019)

ACL

• Ruben Branco, João Rodrigues, Chakaveh Saedi, and António Branco. 2019. Assessing Wordnets with WordNet Embeddings. In Proceedings of the 10th Global Wordnet Conference, pages 253–259, Wroclaw, Poland. Global Wordnet Association.