Here we propose a method for quickly and concretely grounding a large number of gradable adjectives such that their effect can be calculated for entities or events of interest.
we gather human intuitions about the ef-fect of a particular gradable adjective on a given distribution (i.e., mean and standard deviation), independent of the item being modified, and then use this data to fit a linear model.