Fine Tuning Features and Post-processing Rules to Improve Named Entity Recognition ⋆
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BibTeX
@MISC{Ferrández_finetuning,
author = {Óscar Ferrández and Antonio Toral and Rafael Muñoz},
title = {Fine Tuning Features and Post-processing Rules to Improve Named Entity Recognition ⋆},
year = {}
}
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Abstract
Abstract. This paper presents a Named Entity Recognition (NER) system for Spanish which combines the learning and knowledge approaches. Our contribution focuses on two matters: first, a discussion about selecting the best features for a machine learning NER system. Second, an error study of this system which lead us to the creation of a set of general post-processing rules. These issues are explained in detail and then evaluated. The selection of features provides an improvement of around 2.3 % over the results of our previous system while the application of the set of post-processing rules provides an increment of performance which is around 3.6%, reaching finally 83.37 % f-score. 1
