Natural Language Inference for Portuguese Using BERT and Multilingual Information

Cabezudo, Marco Antonio Sobrevilla; Inácio, Marcio Lima; Rodrigues, Ana Carolina; Casanova, Edresson; Sousa, Rogério Figueredo de

doi:10.1007/978-3-030-41505-1_33

Cited by 2 publications

(1 citation statement)

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“…According to this figure, we translated the original sentences from the MSRP corpus to Portuguese, using the machine translation model provided by the Google Translate API (https://cloud.google.com/ translate/). We adopted this model due to the good results achieved by other researchers [34,35] when using it. Next, we translate the Portuguese sentences back to English, because there are no Portuguese reference sentences to evaluate the quality of the translations.…”

Section: Balancing the Assin Corpusmentioning

confidence: 99%

Modeling the Paraphrase Detection Task over a Heterogeneous Graph Network with Data Augmentation

2020

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Paraphrase detection is a Natural-Language Processing (NLP) task that aims at automatically identifying whether two sentences convey the same meaning (even with different words). For the Portuguese language, most of the works model this task as a machine-learning solution, extracting features and training a classifier. In this paper, following a different line, we explore a graph structure representation and model the paraphrase identification task over a heterogeneous network. We also adopt a back-translation strategy for data augmentation to balance the dataset we use. Our approach, although simple, outperforms the best results reported for the paraphrase detection task in Portuguese, showing that graph structures may capture better the semantic relatedness among sentences.

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Section: Balancing the Assin Corpusmentioning

confidence: 99%