Parsing Arabic language is a difficult task given the specificities of the language and given the scarcity of linguistic resources. Linguistic resources such as grammars are very important to any natural language processing application. Unfortunately, the manual construction of these resources is laborious and time-consuming. The use of annotated corpora as a knowledge database might be a solution to a fast construction of a grammar for a given language. In this paper, we began by presenting an overview of our method to automatically induce a probabilistic context free grammar from an Arabic annotated corpus (The Penn Arabic TreeBank). Then we tested the obtained grammar in the parsing task and we expose the evaluation results. Finally we present our vision of a hybrid method for parsing Modern Standard Arabic (MSA) that we believe that it could enhance obtained results.