Semantic Analysis of Arabic Texts Within SAFAR Framework

This paper describes our approach related to the semantic analysis of Arabic texts. We firstly begin by building an Arabic ontology, leveraging the content of the two linguistic resources Arabic WordNet and Arabic VerbNet. We secondly use, for each new analysis, this resource together with some Arabic NLP tools such as the Stanford syntactic parser and the AlKhalil morphological analyzer in order to automatically extract the meaning convoyed by Arabic texts. The semantic is represented by means of the Conceptual Graphs (CGs) formalism. We present also the integration of the semantic analysis technique within the SAFAR framework. This integration has allowed organizing the semantic analysis to be more flexible and efficient. The conducted experiments using this novel semantic analysis are also presented.