This first-in-time adoption of the "supramolecular language" perspective with SMILES strings shows its potential for co-crystallization prediction. While this study only focused on 'two-word sentences' (i.e., molecule pairs), our approach could be extended to supramolecular interactions among multiple molecular partners. As the complexity of the supramolecular tasks increases, we anticipate model "shortcuts" to become more prominent, making explainable AI approaches relevant in exposing those issues. Moreover, extensive datasets with thorough annotations on stereochemistry might further expand the prediction ability of 'supramolecular language' processing approaches based on SMILES strings. Ultimately, extensions of DeepCocrystal might open unexplored opportunities in supramolecular chemistry, e.g. for drug development , materials discovery, and beyond.