They propose DROP, a reading comprehension dataset focused on a limited set of discrete operations such as counting, comparison, sorting and arithmetic.
eQUATe features diverse phenomena that occur naturally in text, including reasoning with approximation, ordinals, implicit quantities and quantifiers, requiring NLI models to reason comprehensively about the interplay between quantities and language.