NLTK tagger for Albanian using iterative approach

This paper presents a research done about a model of tagging for Albanian texts, using the NLTK toolkit. The model uses cascading of three taggers with backoff. We use a dictionary of around 32000 words, together their correspondent POS tags and a set of regular expressions rules too. A lemmatize module is implemented in order to convert nouns and verbs to their lemma. The text is tagged initially with a unigram tagger based on the dictionary. This is used as a baseline tagger for a regular expressions tagger. A correction is made for not correct lemmatized words, creating a third lookup tagger. This tagger will be used with the first and second tagger as backoff.