  The basic unit of meaning on the Semantic Web is the RDF statement, or
triple, which combines a distinct subject, predicate and object to make a
definite assertion about the world. A set of triples constitutes a graph, to
which they give a collective meaning. It is upon this simple foundation that
the rich, complex knowledge structures of the Semantic Web are built. Yet the
very expressiveness of RDF, by inviting comparison with real-world knowledge,
highlights a fundamental shortcoming, in that RDF is limited to statements of
absolute fact, independent of the context in which a statement is asserted.
This is in stark contrast with the thoroughly context-sensitive nature of human
thought. The model presented here provides a particularly simple means of
contextualizing an RDF triple by associating it with related statements in the
same graph. This approach, in combination with a notion of graph similarity, is
sufficient to select only those statements from an RDF graph which are
subjectively most relevant to the context of the requesting process.
