The engineering challenges encountered in adapting Vampire into a reusable component suitable for real-time, multi-query workloads are described, and preliminary performance results comparing the embedded approach with the traditional process-based invocation model used in the original Java-based SigmaKEE are reported.
The results support the feasibility of ontology-driven generation for static-classification systems, whereas arithmetic risk computation and temporal event processing remain better suited to complementary procedural technologies.
Borivoj Bogdanović, S. Nikolić· Computers· 0 citations
This paper looks at the results of testing deontic axioms and systems with example problems using Kripke semantics and possible worlds over accessibility relations in the context of a large ontology, and considers the notion of a sanction in a Contrary To Duty scenario.
Christopher Feener, Adam Pease, Richard Thompson· 0 citations
MOOSEDev, a system designed to give coding agents structured, ontology-grounded project memory, is introduced and a temporal commit-history bootstrap of the author's own codebase, a pre-registered live trial, and lessons learned are described.
Two SRL engines were implemented and evaluated on classical RDF reasoning tasks for soundness, completeness, and speed, finding a usable SRL engine can be built inexpensively on top of a SPARQL engine, with a moderate speed trade-off that a dedicated implementation recovers.
Lander Maes, Bryan-Elliott Tam, Jitse De Smet et al.· 0 citations
OntoExpand is introduced, a new methodology for ontology expansion that uses SPARQL CONSTRUCT queries as an efficient alternative to conventional reasoning techniques that improves performance, reduces computational overhead, is pattern driven allowing a more granular expansion control and seamlessly integrates with SP...
Vitor Lelis, N. Leite, José Carlos et al.· 0 citations
It is argued that retrieval-augmented generation for enterprise finance should be evaluated on auditability alongside accuracy, and the Knowledge-Driven Analytics Framework is presented, which builds ontology-driven knowledge systems through six iterative stages and retrieves evidence via Context-Aware Relevance Propag...
Sergiy Lunyakin· 0 citations
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