Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/32114

Title: Benchmarking natural language inference and semantic textual similarity for portuguese
Authors: Fialho, Pedro
Coheur, Luísa
Quaresma, Paulo
Issue Date: 2020
Publisher: MDPI
Citation: Pedro Fialho, Luı́sa Coheur, and Paulo Quaresma. Benchmarking natural language inference and semantic textual similarity for portuguese. Information, 11(10), 2020.
Abstract: Two sentences can be related in many different ways. Distinct tasks in natural language processing aim to identify different semantic relations between sentences. We developed several models for natural language inference and semantic textual similarity for the Portuguese language. We took advantage of pre-trained models (BERT); additionally, we studied the roles of lexical features. We tested our models in several datasets—ASSIN, SICK-BR and ASSIN2—and the best results were usually achieved with ptBERT-Large, trained in a Brazilian corpus and tuned in the latter datasets. Besides obtaining state-of-the-art results, this is, to the best of our knowledge, the most all-inclusive study about natural language inference and semantic textual similarity for the Portuguese language.
URI: http://hdl.handle.net/10174/32114
Type: article
Appears in Collections:INF - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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