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Title: Back to the Feature, in Entailment Detection and Similarity Measurement for Portuguese
Authors: Fialho, Pedro
Coheur, Luísa
Quaresma, Paulo
Issue Date: 2020
Publisher: Springer
Citation: Pedro Fialho, Luı́sa Coheur, and Paulo Quaresma. Back to the feature, in entailment detec- tion and similarity measurement for portuguese. In Paulo Quaresma, Renata Vieira, San- dra M. Aluı́sio, Helena Moniz, Fernando Batista, and Teresa Gonçalves, editors, Computa- tional Processing of the Portuguese Language - 14th International Conference, PROPOR 2020, Evora, Portugal, March 2-4, 2020, Proceedings, volume 12037 of Lecture Notes in Computer Science, pages 164–173. Springer, 2020.
Abstract: This paper describes a system to identify entailment and quantify semantic similarity among pairs of Portuguese sentences. The system relies on a corpus to build a supervised model, and employs the same features regardless of the task. Our experiments cover two types of features, contextualized embeddings and lexical features, which we eval- uate separately and in combination. The model is derived from a voting strategy on an ensemble of distinct regressors, on similarity measure- ment, or calibrated classifiers, on entailment detection. Applying such system to other languages mainly depends on the availability of cor- pora, since all features are either multilingual or language independent. We obtain competitive results on a recent Portuguese corpus, where our best result is obtained by joining embeddings with lexical features.
Type: article
Appears in Collections:INF - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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