Arabic WordNet (AWN) represents one of the best-known lexical resources for the Arabic language. However, it contains various issues that affect its use in different Natural Language Processing (NLP) applications. Due to resources deficiency, the update of Arabic WordNet requires much effort. There have only been only two updates it was first published in 2006. The most significant of those being in 2013, which represented a significant development in the usability and coverage of Arabic WordNet. This paper provides a study case on the updates of the Arabic WordNet and the development of its contents. More precisely, we present the new content in terms of relations that have been added to the extended version of Arabic WordNet. We also validate and evaluate its contents at different levels. We use its different versions in a Word Sense Disambiguation system. Finally, we compare the results and evaluate them. Results show that newly added semantic relations can improve the performance of a Word Sense Disambiguation system.

When derivational relations deficiency exists in a wordnet, such as the Arabic WordNet, it makes it very difficult to exploit in the natural language processing community. Such deficiency is raised when many wordnets follow the same development path of Princeton WordNet. A rule-based approach for Arabic derivational relations is proposed in this paper to deal with this deficiency. The proposed approach is explained step by step. It involves the gathering of lexical entries that share the same root, into a bag of words. Rules are then used to affect the appropriate derivational relations, i.e. to relate existing words in the AWN, involving part-of-speech switch. The method is implemented using Java. Manual verification by a lexicographer takes place to ensure good results. The described approach gave good results. It could be useful for other morphologically complex languages as well.