PoS-tagging Italian texts with CORISTagger
Fabio Tamburini · 2009
Abstract. This paper presents an evolution of CORISTagger [1], an high-perfor-mance PoS-tagger for Italian developed at the University of Bologna. The sys-tem is composed of a second-order Hidden Markov Model tagger followed by a Transformation Based tagger. The use of such a stacked structure, paired with a powerful morphological analyser based on a large lexicon composed of 120,000 lemmas, allowed the tagger to obtain good performances in the EVALITA 2009 PoS-tagging task. The performances of the tagger and the most common classifi-cation errors are discussed in detail.