Looting and illicit trafficking of cultural objects pose a significant threat to the preservation of cultural heritage. Advanced digital tools for the early detection of such phenomena can play an important role in safeguarding cultural property on a global scale. Fighting illicit trafficking of cultural property in a timely manner is of vital importance, as any loss of time favors smugglers and can seriously undermine the efforts of protecting the cultural heritage. Towards this direction, this paper demonstrates the main functionalities provided by a semantic engine which will apply logical, rule-based reasoning for revealing new relations between the source and the destination points of stolen objects, among the different types of goods and their distribution channels, as well as among diverse structures and activities of traffickers. The semantic engine will display a wide range of alerts alongside a unified graph, thus helping Law Enforcement Agencies to tackle cases of cultural goods crime faster and more effectively.