NLI is standardly treated as a classification task.
in order to interface with existing NLI models, we discretize 10 our collected human judgments by mapping the raw (unnormalized) score (which is between −50 and 50) into K evenly sized bins, where K is equal to the number of classes that were used in the original dataset from which the p/h pair was drawn.