To assess performance of BESMARTS we perform three experiments using either categorical or continuous data. First, we generate a SMARTS hierarchy that replicates the atom typing scheme of GAFF, a popular force field for small drug-like molecules. We then generate a SMARTS hierarchy of the dihedral parameters from the Open Force Field (OpenFF) Sage force field which follows the SMIRNOFF format . Next, we cluster bond lengths of a QM dataset to build a SMARTS hierarchy which shows how this method could be used to initialize a new chemical perception models and design new force fields from scratch. These two cases highlight the dual utility of SMARTS clustering. At times we are interested in assigning SMARTS to a categorical variable, such as a label, or a continuous variable, such as bond lengths, angles, and dihedrals. One may even apply the BE-SMARTS approach to non-bonded parameters and other exotic functional forms that require a perception model for parameterization, such as atomic polarizabilities .