For the product prediction, we use the pretrained Chemformer which was finetuned on our USPTO reactions. Specifically, we used the combined model, which is freely available. This model was trained to learn the sequence-to-sequence task of predicting the product SMILES given the reactant SMILES. Chemformer was fine-tuned for 80 epochs using the default settings. The fine-tuning was done on the tabular version of the same reactions used for training SEAL and was then evaluated on the same hold-out test set. The result of the trained Chemformer model can be seen in Table . This result is comparable with and slightly higher than the results reported in the original publication of 0.918 top-1 accuracy, where the Chemformer is evaluated for forward synthesis prediction. In the original publication Chemformer is also trained on the USPTO for this task but the preprocessing of the datasets differ as our data originates from the CRKG.