Finally, we showcase how the structure of OneStopQA annotations can be used for detailed comparisons between human and machine readers.
we demonstrate that human subjects and a state-of-the-art machine reading comprehension model have similar distributions of erroneous answers, suggesting a deeper link between human and machine readers than previously reported.