Ladder Tagger—Splitting Decision Space to Boost Tagging Quality
Mariusz Paradowski, Adam Radziszewski
DOI: http://dx.doi.org/10.15439/2014F107
Citation: Proceedings of the 2014 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 2, pages 163–169 (2014)
Abstract. This paper describes a part of speech tagger. The tagger is based on a set of probability mixture models. Each mixture model is responsible for tagging of a specific class of words, sharing similar context properties. Probability mixture models contain 25 various mixture components. The tagger is tested on polish language and compared to other available taggers.