This paper describes POS tagging experiments with semi-supervised training as an extension to the (supervised) averaged perceptron algorithm, first introduced for this task by (Collins, 2002). Experiments with an iterative training on standard-sized supervised (manually annotated) dataset (10 6 tokens) combined with a relatively modest (in the order of 10 8 tokens) unsupervised (plain) data in a bagging-like fashion showed significant improvement of the POS classification task on typologically different languages, yielding better than state-of-the-art results for English and Czech (4.12 % and 4.86 % relative error reduction, respectively; absolute accuracies being 97.44 % and 95.89 %).

The aim of this paper is to explore the feasibility of solving the dependency parsing problem using sequence labeling tools. We introduce an algorithm to transform a dependency tree into a tag sequence suitable for a sequence labeling algorithm and evaluate several parameter settings on the standard treebank data. We focus mainly on Czech, as a high-inflective freeword-order language, which is not so easy to parse using traditional techniques, but we also test our approach on English for comparison.

Abstractis article is an extract of the PhD thesis and it extends the article . Several hybrid disambiguation methods are described which combine the strength of hand-written disambiguation rules and statistical taggers. ree 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. e results of the hybrid system are better than any other method tried for Czech tagging so far.

Several hybrid disambiguation methods are described which combine the strength of handwritten disambiguation rules and statistical taggers. Three different statistical (HMM, Maximum-Entropy and Averaged Perceptron) taggers are used in a tagging experiment using Prague Dependency Treebank. The results of the hybrid systems are better than any other method tried for Czech tagging so far.