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Documents authored by Silva, Catarina

Document
DOI: 10.4230/OASIcs.SLATE.2022.3
Question Answering For Toxicological Information Extraction

Authors: Bruno Carlos Luís Ferreira, Hugo Gonçalo Oliveira, Hugo Amaro, Ângela Laranjeiro, and Catarina Silva

Published in: OASIcs, Volume 104, 11th Symposium on Languages, Applications and Technologies (SLATE 2022)

Abstract
Working with large amounts of text data has become hectic and time-consuming. In order to reduce human effort, costs, and make the process more efficient, companies and organizations resort to intelligent algorithms to automate and assist the manual work. This problem is also present in the field of toxicological analysis of chemical substances, where information needs to be searched from multiple documents. That said, we propose an approach that relies on Question Answering for acquiring information from unstructured data, in our case, English PDF documents containing information about physicochemical and toxicological properties of chemical substances. Experimental results confirm that our approach achieves promising results which can be applicable in the business scenario, especially if further revised by humans.
Cite as

Bruno Carlos Luís Ferreira, Hugo Gonçalo Oliveira, Hugo Amaro, Ângela Laranjeiro, and Catarina Silva. Question Answering For Toxicological Information Extraction. In 11th Symposium on Languages, Applications and Technologies (SLATE 2022). Open Access Series in Informatics (OASIcs), Volume 104, pp. 3:1-3:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{ferreira_et_al:OASIcs.SLATE.2022.3,
  author =	{Ferreira, Bruno Carlos Lu{\'\i}s and Gon\c{c}alo Oliveira, Hugo and Amaro, Hugo and Laranjeiro, \^{A}ngela and Silva, Catarina},
  title =	{{Question Answering For Toxicological Information Extraction}},
  booktitle =	{11th Symposium on Languages, Applications and Technologies (SLATE 2022)},
  pages =	{3:1--3:10},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-245-7},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{104},
  editor =	{Cordeiro, Jo\~{a}o and Pereira, Maria Jo\~{a}o and Rodrigues, Nuno F. and Pais, Sebasti\~{a}o},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2022.3},
  URN =		{urn:nbn:de:0030-drops-167493},
  doi =		{10.4230/OASIcs.SLATE.2022.3},
  annote =	{Keywords: Information Extraction, Question Answering, Transformers, Toxicological Analysis}
}
Document
DOI: 10.4230/OASIcs.SLATE.2022.19
Analysing Off-The-Shelf Options for Question Answering with Portuguese FAQs

Authors: Hugo Gonçalo Oliveira, Sara Inácio, and Catarina Silva

Published in: OASIcs, Volume 104, 11th Symposium on Languages, Applications and Technologies (SLATE 2022)

Abstract
Following the current interest in developing automatic question answering systems, we analyse alternative approaches for finding suitable answers from a list of Frequently Asked Questions (FAQs), in Portuguese. These rely on different technologies, some more established and others more recent, and are all easily adaptable to new lists of FAQs, on new domains. We analyse the effort required for their configuration, the accuracy of their answers, and the time they take to get such answers. We conclude that traditional Information Retrieval (IR) can be a solution for smaller lists of FAQs, but approaches based on deep neural networks for sentence encoding are at least as reliable and less dependent on the number and complexity of the FAQs. We also contribute with a small dataset of Portuguese FAQs on the domain of telecommunications, which was used in our experiments.
Cite as

Hugo Gonçalo Oliveira, Sara Inácio, and Catarina Silva. Analysing Off-The-Shelf Options for Question Answering with Portuguese FAQs. In 11th Symposium on Languages, Applications and Technologies (SLATE 2022). Open Access Series in Informatics (OASIcs), Volume 104, pp. 19:1-19:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{goncalooliveira_et_al:OASIcs.SLATE.2022.19,
  author =	{Gon\c{c}alo Oliveira, Hugo and In\'{a}cio, Sara and Silva, Catarina},
  title =	{{Analysing Off-The-Shelf Options for Question Answering with Portuguese FAQs}},
  booktitle =	{11th Symposium on Languages, Applications and Technologies (SLATE 2022)},
  pages =	{19:1--19:11},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-245-7},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{104},
  editor =	{Cordeiro, Jo\~{a}o and Pereira, Maria Jo\~{a}o and Rodrigues, Nuno F. and Pais, Sebasti\~{a}o},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2022.19},
  URN =		{urn:nbn:de:0030-drops-167652},
  doi =		{10.4230/OASIcs.SLATE.2022.19},
  annote =	{Keywords: Natural Language Processing, Portuguese, Question Answering, FAQs, Information Retrieval, Sentence Encoding, Transformers}
}
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