Two of the human datasets, Kent and Minnesota, though collected independently, are based on the same set of 100 cue words established by Kent (1910).
by performing a rank correlation of these two datasets with one another, (each of which was produced by pooling the responses of some 1000 people) we can get a useful upper-bound for correlations: if a computer-based system were to exceed this upper-bound in correlations with either dataset, then we would need to suspect it of over-fitting.