The remainder of the paper proceeds as follows. In section 2 we present a formulation of the key reaction prediction tasks considered in this work. This is followed by a brief review of related work in section 3. We then discuss the data extraction and cleaning methodology, and how ORDerly was used for dataset generation, in section 4. This is followed by experimental validation of these datasets with neural network and transformer architectures in section 5, demonstrating that missing key cleaning steps results in a dataset with contamination, which can inflate key performance metrics. We finally discuss the technical limitations of ORDerly in section 6 and then present our conclusions.