01976nas a2200229   4500000000100000000000100001008004100002260001200043653003200055653001400087653002000101653002100121100002700142700001600169700001400185245007400199856008000273300001000353490000600363520136300369022001401732       2021                            d  c03/202110aNatural Language Processing10aSemantics10aWord Embeddings10aSemantic Lexicon1 aHugo Gonçalo Oliveira1 aTiago Sousa1 aAna Alves00aAssessing Lexical-Semantic Regularities in Portuguese Word Embeddings  uhttps://www.ijimai.org/journal/sites/default/files/2021-02/ijimai_6_5_4.pdf  a34-460 v63 aModels of word embeddings are often assessed when solving syntactic and semantic analogies. Among the latter, we are interested in relations that one would find in lexical-semantic knowledge bases like WordNet, also covered by some analogy test sets for English. Briefly, this paper aims to study how well pretrained Portuguese word embeddings capture such relations. For this purpose, we created a new test, dubbed TALES, with an exclusive focus on Portuguese lexical-semantic relations, acquired from lexical resources. With TALES, we analyse the performance of methods previously used for solving analogies, on different models of Portuguese word embeddings. Accuracies were clearly below the state of the art in analogies of other kinds, which shows that TALES is a challenging test, mainly due to the nature of lexical-semantic relations, i.e., there are many instances sharing the same argument, thus allowing for several correct answers, sometimes too many to be all included in the dataset. We further inspect the results of the best performing combination of method and model to find that some acceptable answers had been considered incorrect. This was mainly due to the lack of coverage by the source lexical resources and suggests that word embeddings may be a useful source of information for enriching those resources, something we also discuss.  a1989-1660