Implementing an efficient part-of-speech tagger
An efficient implementation of a part-of-speech tagger for Swedish is described. The stochastic tagger uses a well-established Markov model of the language. The tagger tags 92 per cent of unknown words correctly and up to 97 per cent of all words. Several implementation and optimization considerations are discussed. The main contribution of this paper is the thorough description of the tagging algorithm and the addition of a number of improvements, The paper contains enough detail for the reader to construct a tagger for his own language. Copyright (C) 1999 John Wiley & Sons, Ltd.
optimization part-of-speech tagging word tagging hidden markov models