Several tools and resources have been developed to deal with Arabic NLP. However, a homogenous and flexible Arabic environment that gathers these components is rarely available. In this perspective, we introduce SAFAR which is a monolingual framework developed in accordance with software engineering requirements and dedicated to Arabic language, especially, the modern standard Arabic and Moroccan dialect. After one decade of integration and development, SAFAR possesses today more than 50 tools and resources that can be exploited either using its API or using its web interface.

The Arabic WordNet project has provided the Arabic Natural Language Processing (NLP) community with the first WordNet-compliant resource. It allowed new possibilities in terms of building sophisticated NLP applications related to this Semitic language. In this paper, we present the new content added to this resource, using semi-automatic techniques, and validated by Arabic native-speaker lexicographers. We also present how this content helps in the implementation of new Arabic NLP applications, especially for Question Answering (QA) systems. The obtained results show the contribution of the added content. The resource, fully transformed into the standard Lexical Markup Framework (LMF), is made available for the community.