论文信息 - Language Independent NER using a Maximum Entropy Tagger

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 | Stephen Clark | S. Clark | J. Curran

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