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Towards analysis on textual inference at ASSIN-2 dataset

In this article, we conduct a preliminary analysis of different methods to address the Textual Entailment Recognition (RTE) task in Portuguese. We use the ASSIN-2 dataset as a benchmark to evaluate our models. Our work combines various textual representation approaches, including bag of words and word embeddings, with machine learning models. Additionally, we present a rule-based approach. Our highest performance was achieved by the BERTimbau-large model fine-tuned on ASSIN-2, which attained an F1 score of 0.89%, positioning it just 1% below the current state-of-the-art. Our ongoing experiment aims to combine our different approaches to leverage their full potential.
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Towards analysis on textual inference at ASSIN-2 dataset

  • DOI: 10.22533/at.ed.9072322125

  • Palavras-chave: NLP, Machine learning, textual inference

  • Keywords: NLP, Machine learning, textual inference

  • Abstract: In this article, we conduct a preliminary analysis of different methods to address the Textual Entailment Recognition (RTE) task in Portuguese. We use the ASSIN-2 dataset as a benchmark to evaluate our models. Our work combines various textual representation approaches, including bag of words and word embeddings, with machine learning models. Additionally, we present a rule-based approach. Our highest performance was achieved by the BERTimbau-large model fine-tuned on ASSIN-2, which attained an F1 score of 0.89%, positioning it just 1% below the current state-of-the-art. Our ongoing experiment aims to combine our different approaches to leverage their full potential.

  • Felipe Oliveira da Silva
  • Giovana Meloni Craveiro
  • Vinícius João de Barros Vanzin
  • Vinícius F. da Silva
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