Signature-based pruning is broadly accepted as an effective way to improve query performance of graph template matching on general labeled graphs. Most existing techniques which utilize signature-based pruning claim its benefits on all datasets and queries. However, the effectiveness of signature-based pruning varies greatly among different RDF datasets and highly related with their dataset characteristics. We observe that the performance benefits from signature-based pruning depend not only on the size of the RDF graphs, but also the underlying graph structure and the complexity of queries. This motivates us to propose a flexible RDF querying framework, called RDF-h, which selectively utilizes signature-based pruning by evaluating the characteristics of RDF datasets and query templates. Scalability and efficiency of RDF-h is demonstrated in experimental results using both real and synthetic datasets. Keywords: RDF, Graph Template Matching, Signature-based Pruning