The role-set approach is a new conceptual framework for data integration in multidatabase systems that maintains the materialization autonomy of local database systems and provides users with more accurate information. The role-set approach presents the answer to a query as a set of relations where the distinct intersections between the relations corresponding to the various roles played by an entity. In this paper we show how the basic role-based approach can be extended in the absence of information about the multidatabase keys (global IDs). We propose a strategy based on ranked role-sets that makes use of a semantic integration procedure based on neural networks to determine candidate global IDs. The data integration and query processing steps then produce a number of role-sets, ranked by the similarity of the candidate IDs.