Although a large number of NMR spectra certainly exist, the majority of these are in a form not readily utilized by ML methods. NMR data and the assignment of experimental shifts to specific atoms in molecular structures are processed and reported in a variety of formats that are difficult to parse automatically. Additionally, the literature contains assignment errors, incompletely recorded spectral data, and partially assigned structures. Manually-curated datasets have thus featured heavily in the development of predictive models for chemical shifts, requiring considerable effort and expertise to build and maintain. The NMRShiftDB 51 stands as an exception to this approach, being an open-submission and open-access database containing around 400,000 experimental 13 C chemical shifts. However, the frequency of incorrect assignments has been debated in the literature, and incomplete annotation of stereochemistry affects a significant proportion of chiral molecules contained in this dataset.