For the datasets that extract the components from the reaction string, overall top-3 accuracy is less than 25% across solvents and agents. While not directly comparable, our overall accuracy is lower than what Gao et al. achieved with 50.1% top-3 accuracy across catalysts, solvents and agents. However, Gao et al. trained on approximately ten million reactions, while we train on less than four percent of that (⇠350k). As shown in Figure , we see consistent increases in AIB (%) with the number of data points for the dataset which uses reaction strings and deletes rare reactions, and this scaling performance indicates that as ORD grows, better performance could be achieved, even with potentially fewer data points than used in the paper by Gao et al.