We describe a simple approach to named-entity recognition (NER), aimed initially at the Dutch language, but potentially applicable to other languages. Our NER system employs a two-stage architecture, with handcrafted but dataset-independent features for both stages, and is on a par with state-of-the-art systems described in the literature. Notably, our approach does not depend on language-specific assets such as gazetteers. The resulting system is quite fast and is implemented in less than 500 lines of code. © 2012 Springer-Verlag.
CITATION STYLE
Buitinck, L., & Marx, M. (2012). Two-stage named-entity recognition using averaged perceptrons. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7337 LNCS, pp. 171–176). https://doi.org/10.1007/978-3-642-31178-9_17
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