Second, chemical compositions in texts were anonymized (e.g., they were replaced with "This crystal" or the phrases in Table ), because the existence of compositions can make the training obvious: The nodes of a crystal graph have features specific to the atoms, whereas the composition in the corresponding text also has the corresponding word-embedding vectors, where the text encoder we adopted tends to tokenize the compositions into the element symbols. These features can be leaked and trivially converted from one to another. In addition, the element symbols were replaced with "[METAL]", "[NONMETAL]", or "[METALLOID]", according to the attribution of each element, and the local coordinations of atoms or clusters were replaced with the word "[POLYHEDRA]". The last replacement may not fully represent all types of coordinations such as ligands, but the words replacing chemical entities are arbitrary. These replacements also prevent possible leaks between each graph and text, but the other important aspect is to define the abstraction level of the chemical entities, rather than the geometric ones, which are the focus of this study.