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.
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CITATION STYLE
Moreno, I., Moreda, P., & Romá-Ferri, M. T. (2015). MaNER: A medicAl named entity recogniser. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9103, pp. 418–423). Springer Verlag. https://doi.org/10.1007/978-3-319-19581-0_40
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