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LDK R Logics for Data and Knowledge Representation ClassL (part 3): Reasoning with an ABox 1.

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Presentation on theme: "LDK R Logics for Data and Knowledge Representation ClassL (part 3): Reasoning with an ABox 1."— Presentation transcript:

1 LDK R Logics for Data and Knowledge Representation ClassL (part 3): Reasoning with an ABox 1

2 Outline  World descriptions, assertions (ABox)  Reasoning with the ABox  Satisfiability/Consistency  Instance checking  Instance retrieval  Concept realization  Eliminating the ABox: Reducing to DPLL reasoning  Closed and open world assumptions 2

3 ABox, syntax  The second component of the knowledge base is the world description, the ABox.  In an ABox one introduces individuals, by giving them names, and one asserts properties about them.  We denote individual names as a, b, c,…  An assertion with concept C is called concept assertion (or simply assertion) in the form: C(a), C(b), C(c), … 3 Student(paul) Professor(fausto) To be read: paul belongs to (is in) Student fausto belongs to (is in) Professor ABOX :: REASONING WITH AN ABOX :: ELIMINATING THE ABOX :: ASSUMPTIONS

4 ABox, semantics  We give semantics to ABoxes by extending interpretations to individual names  An interpretation I: L  ∆ I not only maps atomic concepts to sets, but in addition it maps each individual name a to an element a I ∈ ∆ I, namely I(a) = a I ∈ ∆ I  Unique name assumption (UNA). We assume that distinct individual names denote distinct objects in the domain NOTE: ∆ I denotes the domain of interpretation, a denotes the symbol used for the individual (the name), while a I is the actual individual of the domain. 4 ABOX :: REASONING WITH AN ABOX :: ELIMINATING THE ABOX :: ASSUMPTIONS

5 ABox, semantics ∆ I = {Fausto, Jack, Paul, Mary} We mean that: I(paul) ∈ I(Student) I(fausto) ∈ I(Professor) I(paul) = Paul I(fausto) = Fausto I (Professor) = {Fausto} I (Student) = {Jack, Paul, Mary} 5 A Student(paul) Professor(fausto) ABOX :: REASONING WITH AN ABOX :: ELIMINATING THE ABOX :: ASSUMPTIONS

6 Individuals in the TBox  Sometimes, it is convenient to allow individual names (also called nominals) not only in the ABox, but also in the TBox  They are used to construct concepts. The most basic one is the “set” constructor, written: {a 1,…,a n } It defines a concept, without giving it a name, by enumerating its elements, with the semantics: {a 1,…,a n } I = {a 1 I,…,a n I } 6 Student ≡ {Jack, Paul, …, Mary}(the name is optional) ABOX :: REASONING WITH AN ABOX :: ELIMINATING THE ABOX :: ASSUMPTIONS

7 Reasoning Services  Given an ABox A, we can reason (w.r.t. a TBox T) about the following:  Satisfiability/Consistency: An ABox A is consistent with respect to T if there is an interpretation I which is a model of both A and T.  Instance checking: checking whether an assertion C(a) is entailed by an ABox, i.e. checking whether a belongs to C. A ⊨ C(a) if every interpretation that satisfies A also satisfies C(a).  Instance retrieval: given a concept C, retrieve all the instances a which satisfy C.  Concept realization: given a set of concepts and an individual a find the most specific concept(s) C (w.r.t. subsumption ordering) such that A ⊨ C(a). 7 ABOX :: REASONING WITH AN ABOX :: ELIMINATING THE ABOX :: ASSUMPTIONS

8 Reasoning via expansion of the ABox  Reasoning services over an ABox w.r.t. an acyclic TBox can be reduced to checking an expanded ABox.  We define the expansion of an ABox A with respect to T as the ABox A’ that is obtained from A by replacing each concept assertion C(a) with the assertion C’(a), with C’ the expansion of C with respect to T.  A is consistent with respect to T iff its expansion A’ is consistent  A is consistent iff A is satisfiable (*), i.e. non contradictory. (*) in PL, under the usual translation, with C(a) considered as a proposition different from C(b) 8 ABOX :: REASONING WITH AN ABOX :: ELIMINATING THE ABOX :: ASSUMPTIONS

9 Reasoning via expansion 9 T Undergraduate ⊑  Teach Bachelor ≡ Student ⊓ Undergraduate Master ≡ Student ⊓  Undergraduate PhD ≡ Master ⊓ Research Assistant ≡ PhD ⊓ Teach Assistant(Rui) PhD(Rui) Teach(Rui) Master(Rui) Research(Rui) Student(Rui)  Undergraduate(Rui) A Master(Chen) PhD(Enzo) Assistant(Rui) Master(Chen) Student(Chen)  Undergraduate(Chen) PhD(Enzo) Master(Enzo) Research(Enzo) Student(Enzo)  Undergraduate(Enzo) ABOX :: REASONING WITH AN ABOX :: ELIMINATING THE ABOX :: ASSUMPTIONS  The expansion of A w.r.t. T:

10 Consistency 10 TA Parent ≡ Mother ⊔ FatherMother(Mary) Father ≡ Male ⊓ hasChildFather(Mary) Mother ≡ Female ⊓ hasChild Male ≡ Person ⊓  Female A is not consistent w.r.t. T: In fact, from the expansion of T we get that Mother and Father are disjoint. A is consistent (w.r.t. the empty TBox, no constraints) ABOX :: REASONING WITH AN ABOX :: ELIMINATING THE ABOX :: ASSUMPTIONS  Satisfiability/Consistency: An ABox A is consistent with respect to T if there is an interpretation I which is a model of both A and T.  We simply say that A is consistent if it is consistent with respect to the empty TBox

11 Instance checking 11 Consider T and A from the previous example. Is Phd(Rui) entailed? YES! The assertion is in the expansion of A. ABOX :: REASONING WITH AN ABOX :: ELIMINATING THE ABOX :: ASSUMPTIONS  Instance checking: checking whether an assertion C(a) is entailed by an ABox, i.e. checking whether a belongs to C.  A ⊨ C(a) if every interpretation that satisfies A also satisfies C(a).  A ⊨ C(a) iff A ⋃ {  C(a)} is inconsistent

12 Instance retrieval 12 Consider T and A from the previous example. Find all the instances of  Undergraduate Looking at the expansion of A we have {Chen, Enzo, Rui} ABOX :: REASONING WITH AN ABOX :: ELIMINATING THE ABOX :: ASSUMPTIONS  Instance retrieval: given a concept C, retrieve all the instances a which satisfy C.  Implementation: A trivial, but not optimixed implementation consists in doing instance checking for all instances.

13 Concept realization 13 ABOX :: REASONING WITH AN ABOX :: ELIMINATING THE ABOX :: ASSUMPTIONS  Concept realization: given a set of concepts and an individual a find the most specific concept(s) C (w.r.t. subsumption ordering) such that A ⊨ C(a).  Dual problem of Instance retrieval  Implementation: A trivial, but not optimixed implementation consists in doing instance checking for all concepts.

14 Concept realization Consider T and A from the previous example. Given the instance Rui, and the concept set {Student, PhD, Assistant} find the most specific concept C such that A ⊨ C(Rui) Rui is in the extension of all the concepts above. The following chain of subsumptions holds: Assistant ⊑ PhD ⊑ Student Therefore, the most specific concept is Assistant. 14 T Undergraduate ⊑  Teach Bachelor ≡ Student ⊓ Undergraduate Master ≡ Student ⊓  Undergraduate PhD ≡ Master ⊓ Research Assistant ≡ PhD ⊓ Teach A Master(Chen) PhD(Enzo) Assistant(Rui) ABOX :: REASONING WITH AN ABOX :: ELIMINATING THE ABOX :: ASSUMPTIONS

15 Eliminating the ABox  RECALL: ABoxes contain assertions of the form C(a).  To eliminate the ABox we need to create a corresponding concept for each assertion, e.g. of the form C-a and a new axiom C-a ⊑ C.  This causes an exponential blow up. 15 A = {Master(Chen), Master(Paul), PhD(Enzo), PhD(Ronald), Assistant(Rui)} New concepts: Master-Chen, Master-Paul, PhD-Enzo, PhD-Ronald, Assistant-Rui Their interpretation is the singleton set containing the individual. T is extended with: {Master-Chen ⊑ Master, PhD-Enzo ⊑ PhD, Assistant-Rui ⊑ Assistant} ABOX :: REASONING WITH AN ABOX :: ELIMINATING THE ABOX :: ASSUMPTIONS

16 Eliminating the ABox: the algorithm  It is always possible to reduce reasoning problems w.r.t. an acyclic TBox T and an ABox A to problems without them. See for instance the algorithm for subsumption (all the others can be reduced to it).  Input: a TBox T, an ABox A, the two concepts C and D  Output: true if C ⊑ D holds or false otherwise boolean function IsSubsumedBy(T, A, C, D) { A’ = Expand(A, T); T’ = ConvertAssertions(T, A’); return IsSubsumedBy(T’, C, D) ; } 16 ABox expansion ABox elimination DPLL Reasoning by eliminating T’. (see previous lesson) ABOX :: REASONING WITH AN ABOX :: ELIMINATING THE ABOX :: ASSUMPTIONS

17 Closed and Open world assumptions  Closed world Assumption CWA (in Databases): anything which is not explicitly asserted is false  Open World Assumption OWA (in Abox): anything which is not explicitly asserted (positive or negative) is unknown NOTE: a Database has/is one model. Query answering is model checking. NOTE: an ABox has a set of models. Query answering is satisfiability. NOTE: In ABoxes we use OWA. 17 ABOX :: REASONING WITH AN ABOX :: ELIMINATING THE ABOX :: ASSUMPTIONS


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