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Language independent NER using a unified model of internal and contextual evidence Export

by: Silviu Cucerzan, David Yarowsky
In COLING-02: proceedings of the 6th conference on Natural language learning (2002), pp. 1-4.

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This paper investigates the use of a language independent model for named entity recognition based on iterative learning in a co-training fashion, using word-internal and contextual information as independent evidence sources. Its bootstrapping process begins with only seed entities and seed contexts extracted from the provided annotated corpus. F-measure exceeds 77 in Spanish and 72 in Dutch.


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