Part-Of-Speech (POS) tagging, including tokenization and sentence splitting, is the first step in all Natural Language Processing chain. It usually requires substantial efforts to annotate corpora and produce lexicons. However, when these language resources are missing like in Occitan, rather than concentrate the effort in creating them, methods are settled to adapt existing rich-resourced languages tagger. For this to work, these methods exploit the etymologic proximity of the under-resourced language and a rich-resourced language. In this article, we focus on Occitan, which shares similarities with several romance languages including French and Castillan. The method consists in running existing morpho-syntactic tools, here Tree Tagger, on Occitan texts with first a translation of the frequent words in a rich-resourced language. We performed two distinct experimentations, one exploiting similarities between Occitan and French and the second exploiting similarities between Occitan and Castillan. This method only requires the listing of the 300 most frequent words (based on corpus) to construct two bilingual lexicons (Occitan/French and Occitan/Castillan). Our results are better than those obtained with the Apertium tagger using a larger lexicon.