OWLAPI 在子类断言上设置 DataProperty 严格值
OWLAPI set DataProperty strict value on subclass assertion
我可以使用此代码创建受限数据范围:
public void testDatatypeRestriction() throws OWLException {
OWLOntologyManager m = create();
OWLOntology o = m.createOntology(EXAMPLE_IRI);
// Adults have an age greater than 18.
OWLDataProperty hasAge = df.getOWLDataProperty(IRI.create(EXAMPLE_IRI + "hasAge"));
// Create the restricted data range by applying the facet restriction
// with a value of 18 to int
OWLDataRange greaterThan18 = df.getOWLDatatypeRestriction(df.getIntegerOWLDatatype(), OWLFacet.MIN_INCLUSIVE, df
.getOWLLiteral(18));
// Now we can use this in our datatype restriction on hasAge
OWLClassExpression adultDefinition = df.getOWLDataSomeValuesFrom(hasAge, greaterThan18);
OWLClass adult = df.getOWLClass(IRI.create(EXAMPLE_IRI + "#Adult"));
OWLSubClassOfAxiom ax = df.getOWLSubClassOfAxiom(adult, adultDefinition);
m.applyChange(new AddAxiom(o, ax));
}
现在我需要知道如何以编程方式将 class 定义为具有严格值的数据属性断言的子 class :
Alex:owlClass
HasAge:DataProperty
Alex HasAge value 35
P.S:两个答案都是 correct.but @ssz 答案更接近问题的答案,它适用于隐士和颗粒推理机。
在像 hasAge xsd:integer [>=20 , <=20 ]
这样的公理上进行颗粒推理似乎存在一些问题。参见 here
屏幕截图显示 8.4.3 Literal Value Restriction, see also OWL2 Quick Guide, Data Property Restrictions。
编程方式如下所示:
String EXAMPLE_IRI = "
OWLDataFactory df = m.getOWLDataFactory();
OWLDataProperty hasAge = df.getOWLDataProperty(IRI.create(EXAMPLE_IRI + "hasAge"));
OWLClass adult = df.getOWLClass(IRI.create(EXAMPLE_IRI + "Adult"));
// SubClassOf(:Adult DataHasValue(:hasAge "35"^^xsd:integer))
OWLAxiom ax = df.getOWLSubClassOfAxiom(adult, df.getOWLDataHasValue(hasAge, df.getOWLLiteral(35)));
System.out.println(ax);
System.out.println("---------------");
OWLOntology ont = m.createOntology();
ont.add(ax);
ont.saveOntology(new ManchesterSyntaxDocumentFormat(), System.out);
我可以使用此代码创建受限数据范围:
public void testDatatypeRestriction() throws OWLException {
OWLOntologyManager m = create();
OWLOntology o = m.createOntology(EXAMPLE_IRI);
// Adults have an age greater than 18.
OWLDataProperty hasAge = df.getOWLDataProperty(IRI.create(EXAMPLE_IRI + "hasAge"));
// Create the restricted data range by applying the facet restriction
// with a value of 18 to int
OWLDataRange greaterThan18 = df.getOWLDatatypeRestriction(df.getIntegerOWLDatatype(), OWLFacet.MIN_INCLUSIVE, df
.getOWLLiteral(18));
// Now we can use this in our datatype restriction on hasAge
OWLClassExpression adultDefinition = df.getOWLDataSomeValuesFrom(hasAge, greaterThan18);
OWLClass adult = df.getOWLClass(IRI.create(EXAMPLE_IRI + "#Adult"));
OWLSubClassOfAxiom ax = df.getOWLSubClassOfAxiom(adult, adultDefinition);
m.applyChange(new AddAxiom(o, ax));
}
现在我需要知道如何以编程方式将 class 定义为具有严格值的数据属性断言的子 class :
Alex:owlClass
HasAge:DataProperty
Alex HasAge value 35
P.S:两个答案都是 correct.but @ssz 答案更接近问题的答案,它适用于隐士和颗粒推理机。
在像 hasAge xsd:integer [>=20 , <=20 ]
这样的公理上进行颗粒推理似乎存在一些问题。参见 here
屏幕截图显示 8.4.3 Literal Value Restriction, see also OWL2 Quick Guide, Data Property Restrictions。 编程方式如下所示:
String EXAMPLE_IRI = "
OWLDataFactory df = m.getOWLDataFactory();
OWLDataProperty hasAge = df.getOWLDataProperty(IRI.create(EXAMPLE_IRI + "hasAge"));
OWLClass adult = df.getOWLClass(IRI.create(EXAMPLE_IRI + "Adult"));
// SubClassOf(:Adult DataHasValue(:hasAge "35"^^xsd:integer))
OWLAxiom ax = df.getOWLSubClassOfAxiom(adult, df.getOWLDataHasValue(hasAge, df.getOWLLiteral(35)));
System.out.println(ax);
System.out.println("---------------");
OWLOntology ont = m.createOntology();
ont.add(ax);
ont.saveOntology(new ManchesterSyntaxDocumentFormat(), System.out);