NERP-CRF: A tool for the named entity recognition using conditional random fields

  • Daniela Oliveira F. do Amaral Pontifícia Universidade Católica do Rio Grande do Sul
  • Renata Vieira Pontifícia Universidade Católica do Rio Grande do Sul

Abstract

Conditional Random Fields (CRF) is a probabilistic method for structured prediction which has been widely applied in various areas such as Natural Language Processing (NLP), including the Named Entity Recognition (NER), computer vision, and bioinformatics. Therefore, this paper proposes to perform the task of applying the method CRF NER and an evaluation of its performance based on the corpus of HAREM. In summary, the system NERP-CRF achieved the best Precision results when compared to the systems evaluated in the same corpus, proving to be a competitive and effective system.

Published
2014-07-31
How to Cite
Amaral, D. O. F. do, & Vieira, R. (2014). NERP-CRF: A tool for the named entity recognition using conditional random fields. Linguamática, 6(1), 41-49. Retrieved from https://linguamatica.com/index.php/linguamatica/article/view/v6n1-03
Issue
Vol. 6 No. 1
Section
Simpósio de Tecnologia da Informação e Linguagem Humana, 2013

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