Abstract:  Ontology debugging is one of the non－standard reasoning tasks in artificial intelligence，which is very important for the ontology engineering.Ontology debugging is mainly used to find out the interpretations which may cause the logical conflicts in ontologies，and further revise the ontologies to eliminate these conflicts.Technically，calculating minimal unsatisfiability－preserving sub－TBox(MUPS)is the core issue in the ontology debugging.The existing work of MUPS calculation investigates two approaches：one based on modifying the internal of a description logic reasoner(the “glass－box” technology)，and other based on using an unmodified external reasoner(the “black－box” technology)．In our work，one method using syntactic relevance and associate interpretation is proposed to calculate the MUPS for the unsatisfiable classes and terminologies.This method is based on the traditional black－box technology，and further optimizes the expansion and prune procedure in the traditional black－box technology.Firstly，we extend the candidate unsatisfiable sub－TBox by adding the axioms which are structurally relevant with the axioms that contain unsatisfiable classes.By doing this，we can eliminate the irrelevant axioms for the satisfiability to the extent，which may reduce the size of the axioms in terminologies to be checked.Then，the MUPS calculation can be seen as the procedure of seeking the critical axioms in the MUPS.In this procedure，we propose the definition of the associate interpretation，and the associate interpretation is introduced to construct special interpretation which can be used to check the satisfaction of axioms in candidate minimal unsatisfiable sub－TBox.And the number of reasoner call is reduced and further the reasoning problem in each iteration is also simplified.Finally，we realize the algorithm and compare it with the optimizations of the black box algorithm.The experimental results show that the proposed method can effectively improve the efficiency of MUPS calculation in the terminology.