critical role in advancing the field. And there have been a number of efforts in this direction. , for example, develop a dataset for open-domain question answering;  and do so for reading comprehension (RC); and   and , for the related task of answering cloze questions [@winograd1972understanding; @levesque2011winograd]. To create these datasets, either crowdsourcing or [*(semi-)synthetic*]{} approaches are used. The (semi-)synthetic datasets (e.g., ) are large in size and cheap to obtain; however, they do not share the same characteristics as explicit QA/RC questions [@rajpurkar2016squad]. In comparison, high-quality [*crowdsourced*]{} datasets are much smaller in size, and the annotation process is quite expensive because the labeled examples require expertise and careful design [@danqi2016exam].

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[ ^(1)^*Tesla* was renowned for *his* achievements and showmanship, eventually earning *him* a reputation in popular culture as an archetypal “”. ^(2)^*His* earned *him* a considerable amount of money, much of which was used to finance *his* own projects with varying degrees of success. ^(3)^*He* lived most of his life in a series of , through *his* retirement. ^(4)^*Tesla* died on 7 January 1943. ... ]{}\
**Questions**:\
[ – What was Tesla’s reputation in popular culture? ]{}\
[ ** ]{}\
[ – How did Tesla finance his 