Resumo

MERHBEN, Laroussi; ZOUAGHI, Anis  e  ZRIGUI, Mounir. Lexical Disambiguation of Arabic Language: An Experimental Study. Polibits [online]. 2012, n.46, pp.49-54. ISSN 1870-9044.

In this paper we test some supervised algorithms that most of the existing related works of word sense disambiguation have cited. Due to the lack of linguistic data for the Arabic language, we work on non-annotated corpus and with the help of four annotators; we were able to annotate the different samples containing the ambiguous words. Since that, we test the Naïve Bayes algorithm, the decision lists and the exemplar based algorithm. During the experimental study, we test the influence of the window size on the disambiguation quality, the derivation and the technique of smoothing for the (2n+1)-grams. For these tests the exemplar based algorithm achieves the best rate of precision.

Palavras-chave : Supervised algorithms; training data; Naïve Bayes; decision list; exemplar based algorithm; window size.