Question Answering For Toxicological Information Extraction
University of Coimbra · Instituto Pedro Nunes
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…
Citation impact
- FWCI
- 167.89
- Percentile
- 100%
- References
- 0
Authors
5- FBFerreira, Bruno Carlos LuísCorresponding
University of Coimbra
- GOGonçalo Oliveira, Hugo
University of Coimbra
- AHAmaro, Hugo
Instituto Pedro Nunes
- LÂLaranjeiro, Ângela
- SCSilva, Catarina
University of Coimbra
Topics & keywords
- Computer science
- Security token
- Language model
- Generator (circuit theory)
- Task (project management)
- Benchmark (surveying)
- Discriminative model
- Encoder
- Reduced inequalities