A Named Entity Recognition System for Dutch

We describe a Named Entity Recognition system for Dutch that combines gazetteers, handcrafted rules, and machine learning on the basis of seed material. We used gazetteers and a corpus to construct training material for Ripper, a rule learner. Instead of using Ripper to train a complete system, we used many different runs of Ripper in order to derive rules which we then interpreted and implemented in our own, hand-crafted system. This speeded up the building of a hand-crafted system, and allowed us to use many different rule sets in order to improve performance. We discuss the advantages of using machine learning software as a tool in knowledge acquisition, and evaluate the resulting system for Dutch.

• Type: Conference
• Year: 2001
• Where: CLIN
• Authors: Fien De Meulder, Walter Daelemans, Véronique Hoste
• Keywords: CLIN 2001, CLIN 2004, Hand-crafted System, Machine Learning, Named Entity Recognition