2026-07-22T22:29:12Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:16749 2024-03-06T10:31:47Z ddc:004 open_access

Question Answering For Toxicological Information Extraction Ferreira, Bruno Carlos Luís Gonçalo Oliveira, Hugo Amaro, Hugo Laranjeiro, Ângela Silva, Catarina Information Extraction Question Answering Transformers Toxicological Analysis 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Bruno Carlos Luís Ferreira and Hugo Gonçalo Oliveira and Hugo Amaro and Ângela Laranjeiro and Catarina Silva 2022 Is Part Of OASIcs, Volume 104, 11th Symposium on Languages, Applications and Technologies (SLATE 2022) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.SLATE.2022.3 urn:nbn:de:0030-drops-167493 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2022.3 eng https://creativecommons.org/licenses/by/4.0/legalcode