We investigate the influence of the adverb surprisingly on themeaning of the quantity words few and many, which them-selves have been associated with a reading expressing sur-prise. To learn about the meaning contribution of “surprise”,we compare surprisingly with the intensifier incredibly anda compared to phrase explicitly marking surprise. Based onan empirical measure of subjects’ expectations about everydayevents, a Bayesian model uses data from a sentence judgmenttask to infer likely levels of surprise associated with the differ-ent constructions of interest.

People’s beliefs about everyday events are both of theoreti-cal interest in their own right and an important ingredient inmodel building—especially in Bayesian cognitive models ofphenomena such as logical reasoning, future predictions, andlanguage use. Here, we explore several recently used methodsfor measuring subjective beliefs about unidimensional contigu-ous properties, such as the likely price of a new watch. Asa first step towards a way of assessing and comparing beliefelicitation methods, we use hierarchical Bayesian modeling forinferring likely population-level beliefs as the central tendencyof participants’ individual-level beliefs. Three different depen-dent measures are considered: (i) slider ratings of (relative)likelihood of intervals of values, (ii) a give-a-number task, and(iii) choice of the more likely of two intervals of values. Ourresults suggest that using averaged normalized slider ratingsfor binned quantities is a practical and fairly good approxima-tor of inferred population-level beliefs.