OASIcs.SLATE.2021.18.pdf
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Bootstrapping a Data-Set and Model for Question-Answering in Portuguese (Short Paper)
Authors
Alberto Simões 
,
José João Almeida
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Volume:
10th Symposium on Languages, Applications and Technologies (SLATE 2021)
Series: Open Access Series in Informatics (OASIcs)
Conference: Symposium on Languages, Applications and Technologies (SLATE) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2021-08-10
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Nuno Ramos Carvalho, Alberto Simões, and José João Almeida. Bootstrapping a Data-Set and Model for Question-Answering in Portuguese (Short Paper). In 10th Symposium on Languages, Applications and Technologies (SLATE 2021). Open Access Series in Informatics (OASIcs), Volume 94, pp. 18:1-18:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/OASIcs.SLATE.2021.18
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.
Subject Classification
ACM Subject Classification
- Computing methodologies → Discourse, dialogue and pragmatics
Keywords
- Portuguese language
- question answering
- deep learning
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References
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