License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.SLATE.2021.18
URN: urn:nbn:de:0030-drops-144355
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2021/14435/
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Carvalho, Nuno Ramos ; Simões, Alberto ; Almeida, José João

Bootstrapping a Data-Set and Model for Question-Answering in Portuguese (Short Paper)

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OASIcs-SLATE-2021-18.pdf (0.5 MB)

Abstract

Question answering systems are mainly concerned with fulfilling an information query written in natural language, given a collection of documents with relevant information. They are key elements in many popular application systems as personal assistants, chat-bots, or even FAQ-based online support systems.
This paper describes an exploratory work carried out to come up with a state-of-the-art model for question-answering tasks, for the Portuguese language, based on deep neural networks. We also describe the automatic construction of a data-set for training and testing the model.
The final model is not trained in any specific topic or context, and is able to handle generic documents, achieving 50% accuracy in the testing data-set. While the results are not exceptional, this work can support further development in the area, as both the data-set and model are publicly available.

BibTeX - Entry

@InProceedings{carvalho_et_al:OASIcs.SLATE.2021.18,
  author =	{Carvalho, Nuno Ramos and Sim\~{o}es, Alberto and Almeida, Jos\'{e} Jo\~{a}o},
  title =	{{Bootstrapping a Data-Set and Model for Question-Answering in Portuguese}},
  booktitle =	{10th Symposium on Languages, Applications and Technologies (SLATE 2021)},
  pages =	{18:1--18:5},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-202-0},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{94},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Sim\~{o}es, Alberto and Portela, Filipe and Pereira, Maria Jo\~{a}o},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2021/14435},
  URN =		{urn:nbn:de:0030-drops-144355},
  doi =		{10.4230/OASIcs.SLATE.2021.18},
  annote =	{Keywords: Portuguese language, question answering, deep learning}
}

Keywords: Portuguese language, question answering, deep learning
Collection: 10th Symposium on Languages, Applications and Technologies (SLATE 2021)
Issue Date: 2021
Date of publication: 10.08.2021
Supplementary Material: Software (Source Code): https://github.com/nunorc/qaptnet

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