Explaining Query Answers under Inconsistency-Tolerant Semantics over Description Logic Knowledge Bases (Extended Abstract)

Meghyn Bienvenu, Camille Bourgaux, François Goasdoué
2015 International Workshop on Description Logics  
The problem of querying description logic (DL) knowledge bases (KBs) using database-style queries (in particular, conjunctive queries) has been a major focus of recent DL research. Since scalability is a key concern, much of the work has focused on lightweight DLs for which query answering can be performed in polynomial time w.r.t. the size of the ABox. The DL-Lite family of lightweight DLs [10] is especially popular due to the fact that query answering can be reduced, via query rewriting, to
more » ... e problem of standard database query evaluation. Since the TBox is usually developed by experts and subject to extensive debugging, it is often reasonable to assume that its contents are correct. By contrast, the ABox is typically substantially larger and subject to frequent modifications, making errors almost inevitable. As such errors may render the KB inconsistent, several inconsistency-tolerant semantics have been introduced in order to provide meaningful answers to queries posed over inconsistent KBs. Arguably the most well-known is the AR semantics [17], inspired by work on consistent query answering in databases (cf. [4] for a survey). Query answering under AR semantics amounts to considering those answers (w.r.t. standard semantics) that can be obtained from every repair, the latter being defined as an inclusion-maximal subset of the ABox that is consistent with the TBox. A more cautious semantics, called IAR semantics [17] queries the intersection of the repairs and provides a lower bound on AR semantics. The brave semantics [7] , which considers the answers holding in some repair, provides a natural upper bound. This extended abstract presents our work [6] on explaining why a tuple is a (non-)answer to a query under AR, IAR, or brave semantics. The need to equip reasoning systems with explanation services is widely acknowledged by the DL community. Indeed, there have been numerous works on axiom pinpointing, in which the objective is to identify (minimal) subsets of a KB that entail a given TBox axiom (or ABox assertion) [18, 9, 21, 16, 22, 20, 14, 15] . With regards to conjunctive queries (CQs), a proof-theoretic approach to explaining positive answers to CQs over DL-Lite A KBs was introduced in [8], and, more recently, the problem of explaining negative query answers over DL-Lite A
dblp:conf/dlog/BienvenuBG15 fatcat:w2cccxxttraoziawipadc746l4