
We present a novel approach to querying classical inconsistent description logic (DL) knowledge bases by adopting a paraconsistent semantics with the four ‘Belnapian’ values: exactly true (T), exactly false (F), both (B), and neither (N). In contrast to prior studies on paraconsistent DLs, we allow truth value operators in the query language, which can be used to differentiate between answers having contradictory evidence and those having only positive evidence. We present a reduction to classical DL query answering that allows us to pinpoint the precise combined and data complexity of answering queries with values in paraconsistent ALCHI and its sublogics. Notably, we show that tractable data complexity is retained for Horn DLs. We present a comparison with repair-based inconsistency-tolerant semantics, showing that the two approaches are incomparable.
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], FOS: Computer and information sciences, [INFO.INFO-LO] Computer Science [cs]/Logic in Computer Science [cs.LO], Logic in Computer Science, Logic, Databases (cs.DB), Logic in Computer Science (cs.LO), Databases, Artificial Intelligence (cs.AI), Artificial Intelligence, FOS: Mathematics, [INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB], [MATH.MATH-LO] Mathematics [math]/Logic [math.LO], Logic (math.LO)
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], FOS: Computer and information sciences, [INFO.INFO-LO] Computer Science [cs]/Logic in Computer Science [cs.LO], Logic in Computer Science, Logic, Databases (cs.DB), Logic in Computer Science (cs.LO), Databases, Artificial Intelligence (cs.AI), Artificial Intelligence, FOS: Mathematics, [INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB], [MATH.MATH-LO] Mathematics [math]/Logic [math.LO], Logic (math.LO)
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