TALES: Test Set of Portuguese Lexical-Semantic Relations for Assessing Word Embeddings

Hugo Gonçalo Oliveira ^[1] ; Tiago Sousa ^[2] ; Ana Alves ^[1]
1. [1] Universidade de Coimbra
  
  Universidade de Coimbra
  
  Coimbra (Sé Nova), Portugal
2. [2] Instituto Superior de Engenharia de Coimbra
  
  Instituto Superior de Engenharia de Coimbra
  
  Portugal
Localización: Proceedings of the Workshop on Hybrid Intelligence for Natural Language Processing Tasks (HI4NLP 2020) co-located with 24th European Conference on Artificial Intelligence (ECAI 2020): Santiago de Compostela, Spain, August 29, 2020 / coord. por Pablo Gamallo Otero, Marcos García González, Patricia Martin-Rodilla, Martín Pereira Fariña, 2020, págs. 41-47
Idioma: inglés
Enlaces
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Resumen
- Static word embeddings, like word2vec or GloVe, are of- ten 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 in analogy test sets for English. This paper describes the creation of a new test for assessing Portuguese word embeddings, dubbed TALES, with an exclusive focus on lexical-semantic relations, acquired from lexi- cal resources in Portuguese. It further reports on the performance of methods previously used for solving analogies, with pre-trained Por- tuguese word embeddings, when applied to the created dataset, an experiment that revealed that TALES is challenging to solve. Results achieved are briefly discussed, with conclusions that may be useful for developing new approaches for this problem, possibly new em- beddings, as well as future versions of TALES.