I wonder what is the killer feature to be had. If you want highly connected data, you can use graph databases like neptune, neo4j, datomic. If you want logic programming, you still have swi-prolog, or something like picat, eclipse, mercury, which can easily model triples or custom ontology. There's also apache tinkerpop and similar which give querying a more object oriented feel. I see prolog can interop with Jena, but if it can, why not parse & query rdf/owl in prolog itself. Can't prolog do everything sparql can.
RDF, and in particular OWL2 (reformulation of RDF tech based on description logic) is about decidable fragments of first-order logic, whereas Prolog is an existential Horn fragment on terms with Turing-complete extra-logical additions such as negation-as-failure and "cut" hence has undecidable decision problems. I actually think the EU-granted research belittled in another comment did a good job of carving out fragments of FOL for relevant applications with desirable complexities of decision problems. But from a practical PoV, RDF, OWL, and SPARQL is bordering on unusable (starting from the fact that open world semantics alone isn't applicable in many real-world scenarios), though jena and rdflib are working fine. Think about OWL2/description logic as a variable-free representation of axioms with just two logical variables (plus some with three vars such as the axiom of transitivity).
Today there's a renewed interest in Prolog and Datalog, which makes me happy after RDF had captured the field for almost two decades.
Not 100% certain, but I think the killer feature is the ability to manage your own data while exposing semantic representations that external apps can interact with.
The guiding idea behind RDF was (at one point) that users manage their own data while apps they give permission to can use that data.
