# Question Answering For Toxicological Information Extraction

“Question Answering For Toxicological Information Extraction” (2022), by Ferreira, Bruno Carlos Luís et al. Computer Science research paper. Original abstract below, unchanged. No free PDF was found.

- Authors: Ferreira, Bruno Carlos Luís, Gonçalo Oliveira, Hugo, Amaro, Hugo, Laranjeiro, Ângela, Silva, Catarina
- Published: January 1, 2022
- Field: Computer Science
- DOI: https://doi.org/10.4230/oasics.slate.2022.3
- Source: https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2022.3

## 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.

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