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Language Independent NER using a Maximum Entropy Tagger

Named Entity Recognition (NER) systems need to integrate a wide variety of information for optimal performance. This paper demonstrates that a maximum entropy tagger can effectively encode such information and identify named entities with very high accuracy. The tagger uses features which can be obtained for a variety of languages and works effectively not only for English, but also for other languages such as German and Dutch.


James R. Curran and Stephen Clark, Language Independent NER using a Maximum Entropy Tagger. In: Proceedings of CoNLL-2003, Edmonton, Canada, 2003, pp. 164-167. [ps] [ps.gz] [pdf] [bibtex]
Last update: June 11, 2003. erikt@uia.ua.ac.be