Querying Large Linked Data Resources.

. Exploring large complex linked data resources is challenging as it requires not only mastering SPARQL syntax and semantics but also understanding the RDF data model and large ontology vocabularies comprising of thousands of classes, hundreds of properties and millions of URIs for instances of interest. Natural language question answering systems solve the problem, but these are still subjects of research. We describe a compromise in which non-experts specify a graphical query ‘skeleton’ and annotate it with freely chosen words, phrases and entity names. Our system automatically generates a SPARQL query based on the input query skeleton.