Research Article Open Access

Enhancing Brazilian Portuguese Textual Entailment Recognition with a Hybrid Approach

Allan de Barcelos Silva 1 and Sandro José Rigo1
  • 1 Universidade do Vale do Rio dos Sinos - UNISINOS, Brazil

Abstract

Previous work on textual entailment has not fully exploited aspects of deep linguistic relations, which have been shown as containing important information for entailment identification. In this study, we present a new method to compute semantic textual similarity between two sentences. Our proposal relies on the integration of a set of deep linguistic relations, lexical aspects and distributed representational resources. We used our method with a large set of annotated data available from the ASSIN Workshop in the PROPOR 2016 event. The achieved results score among the best-known results in the literature. A perceived advantage of our approach is the ability to generate good results even with a small corpus on training tasks.

Journal of Computer Science
Volume 14 No. 7, 2018, 945-956

DOI: https://doi.org/10.3844/jcssp.2018.945.956

Submitted On: 5 May 2018 Published On: 12 July 2018

How to Cite: de Barcelos Silva , A. & Rigo, S. J. (2018). Enhancing Brazilian Portuguese Textual Entailment Recognition with a Hybrid Approach. Journal of Computer Science, 14(7), 945-956. https://doi.org/10.3844/jcssp.2018.945.956

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Keywords

  • Semantic Textual Similarity
  • Computational Linguistics
  • Textual Entailment
  • Word Embeddings
  • Machine Learning