What is an Ontology Engine?

A semantic reasoner, reasoning engine, rules engine, or simply a reasoner, is a piece of software able to infer logical consequences from a set of asserted facts or axioms. The notion of a semantic reasoner generalizes that of an inference engine, by providing a richer set of mechanisms to work with. The inference rules are commonly specified by means of an ontology language, and often a description language. Many reasoners use first-order predicate logic to perform reasoning; inference commonly proceeds by forward chaining and backward chaining. There are also examples of probabilistic reasoners, including Pei Wang's non-axiomatic reasoning system, Novamente's probabilistic logic network, and Pronto - probabilistic description logic reasoner. Someone wrote in Wiki

I think a better way to put it is that the ontology engine perform morphologies of the ontology web such as graph search, graph expansions, reduction; all operations the ontology garph performed y the ontology ennine. The ontology engine continually morphs the ontology graph such that click thrus and semantic search strings are matched to precision.

The Geeks could construct the entire thing around SQL lite.

How about the Ret Algorithm:

The Rete algorithm provides a generalized logical description of an implementation of functionality responsible for matching data tuples ("facts") against productions ("rules") in a pattern-matching production system (a category of rule engine). A production consists of one or more conditions and a set of actions which may be undertaken for each complete set of facts that match the conditions. Conditions test fact attributes, including fact type specifiers/identifiers. The Rete algorithm exhibits the following major characteristics:

I don't get how the domain of ontology matches with RDF respurce pointers, except the ontolofy ultimately points to a RDF, possibly. But the ontology domain is entirely plan English (or other) words arranged as an indexing system. The ontology system as simple in and outs. In is plan text, which becomes, internally, the raw ontology mesh of the clients. Clients search, or specify, with a partially ordered set of plan language keywords. The result is a list of URL, and possible RDF, pointers, partially displayed. URL, RDF, no where play an internal role inthe onology engine, they are simply atomic outcomes.