This study aims at the implementation and evaluation of techniques for extracting semantic relations from a multilingual aligned corpus. Firstly, our observations will focus on the semantic comparison of translational equivalents in multilingual aligned corpus. From these equivalences, we will try to extract "cliques", which ara maximum complete related sub-graphs, where all units are interrelated because of a probable semantic intersection. These cliques have the advantage of giving information on both the synonymy and polysemy of units, and providing a form of semantic disambiguation. Secondly, we attempt to link these cliques with a semantic lexicon (like WordNet) in order to assess the possibility of recovering, for the Arabic units, a semantic relationships already defined for English, French or Spanish units. These relations would automatically build a semantic resource which would be useful for different applications of NLP, such as Question Answering systems, machine translation, alignment systems, Information Retrieval…etc.
