The ability to efficiently find relevant subgraphs and paths in a large graph to a given query is important in many applications including scientific data analysis, social networks, and business intelligence. Currently, there is little support and no efficient approaches for expressing and executing such queries. This paper proposes a data model and a query language to address this problem. The contributions include supporting the construction and selection of: (i) folder nodes, representing a set of related entities, and (ii) path nodes, representing a set of paths in which a path is the transitive relationship of two or more entities in the graph. Folders and paths can be stored and used for future queries. We introduce FPSPARQL which is an extension of the SPARQL supporting folder and path nodes. We have implemented a query engine that supports FPSPARQL and the evaluation results shows its viability and efficiency for querying large graph datasets.