For the Ullmann dataset, we believe the HTE and literature reactomes are in broad agreement. Gratifyingly, phenanthroline-based and picolinamide-based ligands are present in the best-in-class ligands, which are well known as privileged scaffolds in Ullmann couplings . HiTEA observed that the Ma ligands (DMPAO and PMPBO) were individually less successful than other ligands in the standardized format of this HTE dataset. These ligands are characterized by high yields in the literature which acknowledges that their yields are sensitive to the electronics of the specific ligand-reactant pairing . Thus, it is possible that the true potential of these ligand was masked. Visualization of the ligand space reveals a very narrow scope for ligand choice, perhaps unsurprisingly given the similarity of privileged scaffolds in Ullmann couplings (Fig. and Fig. ). A unique observation for the Ullmann's ligand PCA is that the clustering is confined to the best-in-class ligands, supporting the random forest, z-score-ANOVA-Tukey findings that, for the most part, a few select ligands are useful for good yield outcomes. This outcome highlights the sensitivity of HiTEA's best-and worst-in-class catalyst analysis: despite the similarity in structure of the ligands, key differences in performance were identified, leading to a remarkably subtle overall ranking. The selection of specific solvents within the subreactomes was also intriguing. Although all the solvents identified are known to be good solvents within the literature, it is striking how each solvent's importance varies across subreactomes. Solvent effects are known to play a role in the mechanism of Ullmann couplings, but an exact understanding of which solvents are best for SET vs IAT or for C-N vs C-O coupling is not fully characterized, despite observed preferences . A deeper dive into solvent characteristics is recommended for a more comprehensive understanding of this reactome overall.