Structured Product Labels (SPLs) contain information about drugs that can be valuable to clinical and translational research, especially if it can be linked to other sources that provide data about drug targets, chemical properties, interactions, and biological pathways. Unfortunately, SPLs currently provide coarsely-structured drug information and lack the detailed annotation that is required to support computational use cases. To help address this issue we created LinkedSPLs, a Linked Data resource that extends the "web of drug identity" using information extracted from SPLs. In this paper we describe the mapping that LinkedSPLs provides between SPL active ingredients and DrugBank chemical entities. These mappings were created using three approaches: InChI chemical structure descriptors comparison, exact string matching based on the chemical name, and automatic (unsupervised) linkage identification. Comparison of the approaches found that, while these three approaches are complementary, the automatic approach performs well in terms of precision and recall.