Root Identification Tool for Arabic Verbs

Numerous Arabic morphology systems have been devoted toward morphed requirements of words that are required by other text analyzers. Term rooting is an essential requirement in those systems, yet rooting module in the state-of-the-art morphology systems insufficiently meet that requirement, especially verb term. Consequently, due to termination in stemming term rather than a rooting term. Since the stem of the verb is not the root of the verb, it is not feasible to generate or inference verb's derivations and whole it's surface forms (patterns) such tense, number, mood, person, aspect, and others of verb irregular patterns. Therefore, we propose a new model for identifying the verb's root produced in a tool (RootIT) in order to overcome verb root extraction without disambiguation out of traditional methods, applied in current morphology systems. A major design goal of this system is that it can be used as a standalone tool and can be integrated, in a good manner, with other linguistic analyzers. The adopted approach is a mapping surface verb with full-scale derivative verbs discharged previously in the relational database. Moreover, the proposed system is tested on the adopted dataset from PATB verbs extracted from CoreNLP system. The extracted dataset, containing more than (7950) distinguishes verbs belonging to (1938) different roots. The results obtained outstrip the best-compared system by (2.74%) of high accuracy.