Tagging with Combined Language Models and Large Tagsets

The paper discusses experiments, results, applications and further developments in tagging a highly inflectional language, based on multiple register diversified language models. The texts are accurately disambiguated in terms of a large tagset (611 tags) in two linear-time processing steps (tiered processing). The underlying tagger simultaneously uses multiple register language models and choosing the final annotation is achieved by a combined classifiers decisionmaking procedure.