LX-LR4DistSemEval: a collection of language resources for the evaluation of distributional semantic models of Portuguese

Authors

  • Andreia Querido Faculdade de Ciências da Universidade de Lisboa
  • Rita Carvalho Faculdade de Ciências da Universidade de Lisboa
  • João Rodrigues Faculdade de Ciências da Universidade de Lisboa
  • Marcos Garcia Faculdade de Filologia, Universidade de Coruña
  • João Silva Faculdade de Ciências da Universidade de Lisboa
  • Catarina Correia Faculdade de Ciências da Universidade de Lisboa
  • Nuno Rendeiro Faculdade de Ciências da Universidade de Lisboa
  • Rita Valadas Pereira Faculdade de Ciências da Universidade de Lisboa
  • Marisa Campos Faculdade de Ciências da Universidade de Lisboa
  • António Branco Faculdade de Ciências da Universidade de Lisboa

DOI:

https://doi.org/10.26334/2183-9077/rapln3ano2017a15

Keywords:

distributional semantics, data sets, evaluation, Portuguese

Abstract

In this paper we describe a collection of publicly available data sets for Portuguese that are suitable for the evaluation of distributional semantics models in lexical similarity tasks and in conceptual categorization tasks. These data sets were adapted from English gold-standard test sets, allowing any Portuguese distributional semantics model to be evaluated and also to be compared to mainstream results that have been obtained for this language. We also present an online service that showcases some functionalities of the distributional semantics models.

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Published

2017-09-29

How to Cite

Querido, A., Carvalho, R. ., Rodrigues, J., Garcia, M., Silva, J., Correia, C., … Branco, A. (2017). LX-LR4DistSemEval: a collection of language resources for the evaluation of distributional semantic models of Portuguese. Journal of the Portuguese Linguistics Association, (3), 265–283. https://doi.org/10.26334/2183-9077/rapln3ano2017a15

Issue

No. 3 (2017): Journal of the Portuguese Linguistics Association

Section

Articles

License

Copyright (c) 2017 Andreia Querido, Rita Carvalho, João Rodrigues, Marcos Garcia, João Silva, Catarina Correia, Nuno Rendeiro, Rita Valadas Pereira, Marisa Campos, António Branco

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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