The reference reconciliation problem consists in decid- ing whether different identifiers refer to the same data, i.e., correspond to the same world entity. The L2R sys- tem exploits the semantics of a rich data model, which extends RDFS by a fragment of OWL-DL and SWRL rules. In L2R, the semantics of the schema is translated into a set of logical rules of reconciliation, which are then used to infer correct decisions both of reconcilia- tion and no reconciliation. In contrast with other ap- proaches, the L2R method has a precision of 100% by construction. First experiments show promising results for recall, and most importantly significant increases when rules are added.