Recognizing pharmacovigilance named entities in Brazilian Portuguese with CoreNLP - Cunha, Alexandre M. R.; Belloze, Kele T.; Guedes, Gustavo P. (Anais do Brazilian e-Science Workshop (BreSci); 2019: Anais do XIII Brazilian e-Science Workshop, 2019)
Textual data sources may assist in the detection of adverse events not predicted for a particular drug. However, given the amount of information available in several sources, it is reasonable to adopt a computational approach to analyze these sources to search for adverse events. In this scenario, we created an extension of CoreNLP to process Brazilian Portuguese texts from pharma- covigilance area. We trained three natural language models: a Part-of-speech tagger, a parser and a Named Entity Recognizer. Preliminary results indicate success in generating a dependency tree for phrases in the pharmacovigilance area and in identifying pharmacovigilance named entities.