Title
Two-Stage named-entity recognition using averaged perceptrons
Abstract
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.
Year
DOI
Venue
2012
10.1007/978-3-642-31178-9_17
NLDB
Keywords
Field
DocType
state-of-the-art system,resulting system,language-specific asset,ner system,dutch language,simple approach,two-stage named-entity recognition,two-stage architecture,dataset-independent feature
Architecture,Computer science,Natural language processing,Artificial intelligence,Perceptron,Named-entity recognition,Source lines of code
Conference
Citations 
PageRank 
References 
5
0.48
7
Authors
2
Name
Order
Citations
PageRank
Lars Buitinck11106.31
Maarten Marx2137297.86