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.2022.3
URN: urn:nbn:de:0030-drops-167493
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2022/16749/
Go to the corresponding OASIcs Volume Portal

Ferreira, Bruno Carlos Luís ; Gonçalo Oliveira, Hugo ; Amaro, Hugo ; Laranjeiro, Ângela ; Silva, Catarina

Question Answering For Toxicological Information Extraction

pdf-format:
OASIcs-SLATE-2022-3.pdf (0.7 MB)

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.

BibTeX - Entry

@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.dagstuhl.de/opus/volltexte/2022/16749},
  URN =		{urn:nbn:de:0030-drops-167493},
  doi =		{10.4230/OASIcs.SLATE.2022.3},
  annote =	{Keywords: Information Extraction, Question Answering, Transformers, Toxicological Analysis}
}

Keywords: Information Extraction, Question Answering, Transformers, Toxicological Analysis
Collection: 11th Symposium on Languages, Applications and Technologies (SLATE 2022)
Issue Date: 2022
Date of publication: 27.07.2022

DROPS-Home | Fulltext Search | Imprint | Privacy Published by LZI