Abstract
This paper explores the use of classifier ensembles for the task of named entity recognition
(NER) on a Dutch dataset. Classifiers from 3 classification frameworks, namely
memory-based learning (MBL), conditional random fields (CRF) and support vector machines
(SVM), were trained on 8 different feature sets to create a pool of classifiers from
which an
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