Rather than a single large region in latent space corresponding to ligands with a particular total number of coordinating atoms, ligands of the same number of coordinating atoms are grouped into smaller aggregates. This suggests that the model relies on a more nuanced molecular description to classify ligands beyond the number of coordinating atoms, which is consistent with our chemical understanding that denticity and hapticity alone are not sufficient to identify a ligand's coordinating atoms. The resulting learned representations are more distinct and correspond to ligands that are chemically similar ligand rather than only those with identical denticities or hapticities. This observation is confirmed when analyzing the model's learned representations in terms of average atomic numbers of coordinating atoms (Figure ). We find that ligands grouped together in distinct regions of latent space typically have the same coordinating atoms, indicating that the model is learning to represent ligands in terms of their coordinating motifs and generates a similar learned embedding for ligands with similar coordinating atom environments. The distinct learned representations of the coordinating atoms model provide insight into the model's accurate understanding of coordination chemistry and reveal underlying trends of chemical interest.