This paper describes the multistage process for building Arabic WordNet (ArWn) to be used in mobile device. The goal of this paper is how to create corpus, starting with selecting an annotation task, designing the data with the annotation process, and finally evaluating the results for a particular goal. Therefore, the paper presents designing and implementing bi-lingual lexicon to be used in machine translation and language processing. Consequently, the paper takes into consideration language characteristics in both directions Arabic and English. The proposed system is based on WordNet lexical database with a semantic and commonsense knowledge. The proposed dictionary will be implemented for mobile devices, therefore; the cloud computing will be used in this implementation. Consequently, SQL Azure will be used to solve scalability, and interoperability of mobile users and other methods have been used for both Arabic and English languages. So, the SQL Azure will be used as the cloud database to solve both the scalability in the data with scale terabytes of data to millions of mobile users and the interoperability challenges. The system dictionary is developed and tested in Android mobile platform. Experimental results show that the proposed system has two versionsat work; offline and online. The online approach uses the mobiles computing in the cloud system to reduce the storage complexity of the mobile. Real time test will be used in order to evaluate the system access and respond times to display results.