The aim of textual entailment and paraphrase recognition is to determine whether the meaning of a text fragment can be inferred (is entailed) from the meaning of another text fragment. In this paper, we address the task of automatically recognizing textual entailment (RTE) and paraphrases from text written in the Portuguese language employing supervised machine learning techniques. Firstly, we formulate the task as a multi-class classification problem. We conclude that semantic-based approaches are very promising to recognize textual entailment and that combining data from European and Brazilian Portuguese brings several challenges typical with cross-language learning. Then, we formulate the task as a binary classification problem and demonstrate the capability of the proposed classifier for RTE and paraphrases. The results reported in this work are promising, achieving 0.83 of accuracy on the test data.
CITATION STYLE
Rocha, G., & Lopes Cardoso, H. (2017). Recognizing textual entailment and paraphrases in Portuguese. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10423 LNAI, pp. 868–879). Springer Verlag. https://doi.org/10.1007/978-3-319-65340-2_70
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