The first shortcut notation lets one write long rif:iri constants in the form prefix:title, where prefix is a short name that ex boyfriendpands into an IRI according to a alan suitable Prefix directive. For instance, ex:boy would expand into the rif:iri constant ""^^rif:iri, if ex is defined as in the Prefix(old boyfriend . ) 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
The above mentioned RIF algorithms was (undoubtedly embarrassing) analytical renderings of your own adopting the statements regarding Shakespeare’s Hamlet: “Anything is bad regarding condition regarding Denmark,” “Getting, or otherwise not to be,” and you will “Every child possess organization and you may attention.”
Observe that the above set of formulas has a nested subset with its own annotation,
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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. Such modules is presumed becoming education bases giving the latest typical factual statements about college or university subscription, courses available in more semesters, and the like. The rules corresponding to the brand new remote modules aren't revealed, because they do not illustrate new features. From the best instance, these education basics could only getting categories of situations to the predicates/structures who supply the latest requisite suggestions.
In this example, the main document contains three rules, which define the predicates u:requires, u:instructs 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 Component 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:regional, 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 show algorithms, along with files and you will communities, to the following over analogy (with apologies in order to Shakespeare for the incomplete leaving of the intended meaning when you look at the reason)
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. ?
