As research into disease pathology and cellular function continues to generate vast amounts of data pertaining to protein, gene and small molecule (PGSM) interactions, there exists a critical need to capture these results in structured formats allowing for computational analysis. Although many efforts have been made to create databases that store this information in computer readable form, populating these sources largely requires a manual process of interpreting and extracting interaction relationships from the biological research literature. Being able to efficiently and accurately automate the extraction of interactions from unstructured text, would greatly improve the content of these databases and provide a method for managing the continued growth of new literature being published.