İçeriğe geç

To possess ideal readability, i make use of the notation defined in the [RIF-DTB], that provides shortcuts for creating Iris

To possess ideal readability, i make use of the notation defined in the [RIF-DTB], that provides shortcuts for creating Iris

The first shortcut notation lets one write long rif:iri constants in the form prefix:label, where prefix is a short name that expands into an IRI according to a suitable Prefix directive. For instance, ex:child would expand into the rif:iri constant ""^^rif:iri, if ex is defined as in the Prefix(ex . ) directive below. The second shortcut notation uses angle brackets as a way to shorten the ". "^^rif:iri idiom. For instance, the prevous rif:iri constant can be alternatively represented as < The last shortcut notation lets one write rif:iri constants using IRIs relative to a base, where the base IRI is specified in a directive. For instance, with the directive, below, both and "Yorick"^^rif:iri expand into the rif:iri constant ""^^rif:iri. The example also illustrates attachment of the perfect match ne demek annotations.

The aforementioned RIF algorithms is (undoubtedly embarrassing) logical renderings of your own following comments from Shakespeare’s Hamlet: “Something are bad regarding condition from Denmark,” “To-be, or not getting,” and you may “All the child keeps providers and you may attract.”

Observe that the above set of formulas has a nested subset with its own annotation, , which contains only a global IRI. ?


The first document, below, imports the second document, which is assumed to be located at the IRI In addition, the first document has references to two remote modules, which are located at and respectively. These segments is assumed become degree basics giving the usual information about university enrollment, courses offered in other semesters, and so on. The principles add up to new remote segments are not shown, because they do not show additional features. On greatest instance, such knowledge basics can simply be sets of things towards the predicates/frames that supply brand new called for guidance.

In this example, the main document contains three rules, which define the predicates u:takes, u:teaches and u:popular_course. The information for the first two predicates is obtained by querying the remote modules corresponding to Universities 1 and 2. The rule that defines the first predicate says that if the remote university knowledge base says that a student s takes a course c in a certain semester s then takes(s c s) is true in the main document. The second rule makes a similar statement about professors teaching courses in various semesters. Inside the main document, the external modules are referred to via the terms _univ(1) and _univ(2). The Module directives tie these references to the actual locations. The underscore in front of univ signifies that this is a rif:regional symbol and is a shortcut for "univ"^^rif:local, as defined in [RIF-DTB], Section Constants and Symbol Spaces. Note that the remote modules use frames to represent the enrollment information and predicates to represent course offerings. The rules in the main document convert both of these representations to predicates. The third rule illustrates a use of aggregation. The comprehension variable here is ?Stud and ?Crs is a grouping variable. Note that these are the only free variables in the formula over which aggregation is computed. For each course, the aggregate counts the number of students in that course over all semesters, and if the number exceeds 500 then the course is declared popular. Note also that the comprehension variable ?Stud is bound by the aggregate, so it is not quantified in the Forall-prefix of the rule.

We train formulas, together with data and you will teams, toward adopting the over analogy (having apologies so you’re able to Shakespeare to the imperfect leaving of your own required definition when you look at the reasoning)

The imported document has only one rule, which defines a new concept, u:studentOf (a student is a studentOf of a certain professor if that student takes a course from that professor). Since the main document imports the second document, it can answer queries about u:studentOf as if this concept were defined directly within the main document. ?

Bir yanıt yazın

E-posta adresiniz yayınlanmayacak. Gerekli alanlar * ile işaretlenmişlerdir

Hemen Ara