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Combining Statistical and Rule-Based Approaches to Morphological Tagging of Czech Texts

DOI: 10.2478/v10108-009-0002-x

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Abstract:

This article is an extract of the PhD thesis (Spoustová, 2007) and it extends the article (Spoustová et al., 2007). Several hybrid disambiguation methods are described which combine the strength of hand-written disambiguation rules and statistical taggers. Three different statistical taggers (HMM, Maximum-Entropy and Averaged Perceptron) and a large set of hand-written rules are used in a tagging experiment using Prague Dependency Treebank. The results of the hybrid system are better than any other method tried for Czech tagging so far.

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