The benchmarking case study is conducted on the open-source dataset from the United States Trademark and Patent Office (USPTO), curated by Lowe . This database encompasses over 1 million reactions, thereby being the largest open-source database for chemical reactions. Several smaller databases were curated from the USPTO, one of them being the USPTO-50k dataset . Only consisting of 50,000 reactions, it is considerably smaller in size compared to the entire USPTO. Nevertheless, atom-mapping is provided within the dataset alongside reaction class information for each reaction i.e. each reaction belongs to one of ten superclasses (e.g. protection, oxidation). The USPTO-50k is the preferred dataset for retrosynthesis thanks to its rich data. Particularly, the reaction superclass information has been shown to increase the performance of retrosynthesis prediction . Nonetheless, the reaction type is generally unknown prior to synthesis planning. Hence, for training retrosynthesis frameworks, the reaction type is disregarded. Since no information is provided about reaction conditions, the frameworks are trained on the single product USPTO-50k dataset. Furthermore, most retrosynthesis frameworks are not capable of predicting reagents (catalysts/solvent) alongside the reactants. In this paper, precursor and reactant are thus used interchangeably. The dataset follows an 80/10/10 split, leaving 5007 reactions for the benchmarking case study. To extract the predictions for all 5007 products from the retrosynthesis framework, the following steps are followed: