Recognizing pharmacovigilance named entities in Brazilian Portuguese with CoreNLP

  • Alexandre M. R. Cunha CEFET/RJ
  • Kele T. Belloze CEFET/RJ
  • Gustavo P. Guedes CEFET/RJ


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.

Palavras-chave: named entity recognition, pharmacovigilance, Brazilian Portuguese


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CUNHA, Alexandre M. R.; BELLOZE, Kele T.; GUEDES, Gustavo P.. Recognizing pharmacovigilance named entities in Brazilian Portuguese with CoreNLP. In: BRAZILIAN E-SCIENCE WORKSHOP (BRESCI), 13. , 2019, Belém. Anais do XIII Brazilian e-Science Workshop. Porto Alegre: Sociedade Brasileira de Computação, june 2019 . p. 76-79. DOI: