MaNER: A MedicAl Named Entity Recogniser

Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9103)

Abstract

This paper describes a medicinal products and active ingredients named entity recogniser (MaNER) for Spanish technical documents. This rule-based system uses high quality and low-maintenance lexicons. Our results (F-measure 90 %) proves that dictionary-based approaches, without any deep natural language processing (e.g. POS tagging), can achieve a high performance in this task. Our system obtains better results when compared to similar systems.

Keywords

Named Entity Recognition Lexicon Medicinal product Active ingredient Spanish 
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Notes

Acknowledgments

This paper has been partially supported by the Spanish Government (grant no. TIN2012-38536-C03-03 and TIN2012-31224)

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Isabel Moreno
    • 1
  • Paloma Moreda
    • 1
  • M. T. Romá-Ferri
    • 2
  1. 1.Department of Software and Computing SystemsUniversity of AlicanteAlicanteSpain
  2. 2.Department of NursingUniversity of AlicanteAlicanteSpain

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