Benchmark of Arabic morphological analyzers challenges and solutions

Arabic Natural Language Processing (ANLP) has known an important development during the last decade. Nowadays, several ANLP tools are already developed such as morphological analyzers. These analyzers are often used in more advanced applications such as syntactic parsers, search engines, machine translation systems, etc. However, the choice of a morphological analyzer to use, among others, can be difficult for researchers if they ignore its metrics. In this article, we present the challenges of the benchmark of Arabic morphological analyzers. We present also our solution developed in Java, which allows the benchmark by returning the most common metrics, namely the accuracy, precision, f-measure and execution time. This solution has the advantage of being cross-platform, flexible and allows to be extended to cover new morphological analyzers to compare.