Parsing Arabic Verbal Sentence Using Grammar Ontology

Abstract

We build a model to parse the Arabic verbal sentence based on Arabic grammar ontology. The ontology conceptualizes the Arabic verbal sentence through the representation of grammar parsing classes, verb properties, and conjunction checking. By populating the ontology with verbal sentences and adding grammar rules, we form a verbal sentence knowledge base. The parsing model is supported by morphological analysis for sentence syntactic analysis and supported by Arabic synonyms extractor for deriving synonyms. We have implemented the model and have provided it with a user interface where the user can enter a sentence to be parsed and obtains the parsing results. The interface has the options to partially or totally add diacritics to the words of the sentence and it has the possibility to remove ambiguity by choosing the most appropriate analysis from lexicon results. To evaluate the model, we have selected a representative set of Arabic verbal sentences from Arabic grammar books that represent all the possibilities of a verbal sentence. We have performed several parsing tests on these sentences with and without diacritics. The results prove the ability of the model to parse the various forms of the verbal sentence. The accuracy increases when the sentence is diacriticized while avoiding free word order and following the Arabic verbal sentence general form.