Nymble: a High-Performance Learning Name-finder
Daniel M. Bikel, Scott Miller, Richard Schwartz, Ralph Weischedel
Abstract
This paper presents a statistical, learned approach to finding names and other non-recursive entities in text (as per the MUC-6 definition of the NE task), using a variant of the standard hidden Markov model. We present our justification for the problem and our approach, a detailed discussion of the model itself and finally the successful results of this new approach.
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