Handling partially specified inconsistent information is a major challenge, especially when balancing the richness of query answers with the need to control computational complexity. We address this challenge by proposing an efficient method for computing a consistent and enriched fragment of data, known as a repair, within knowledge bases that rely on a stable terminological component and incorporate partially ordered uncertainty in the data (ABox). Our approach, grounded in possibility theory, avoids exhaustive enumeration of conflicts or justifications by applying a positive deductive closure directly to the partially ordered ABox. This enables repair computation through simple consistency checks over data subsets, ensuring tractability while supporting an extended set of plausible inferences. Beyond this main contribution on efficient repair computation, we briefly introduce a semantic characterisation of repairs that generalises the classical notion of models for consistent knowledge bases. Finally, we present an experimental evaluation against existing possibilistic approaches, demonstrating both practical effectiveness and computational benefits.