Investigating the role of entropy in sentence processing

Abstract

We outline four ways in which uncertainty might affect comprehension difficulty in human sentence processing. These four hypotheses motivate a self-paced reading experiment, in which we used verb subcategorization distributions to manipulate the uncertainty over the next step in the syntactic derivation (single step entropy) and the surprisal of the verb's complement. We additionally estimate wordby- word surprisal and total entropy over parses of the sentence using a probabilistic context-free grammar (PCFG). Surprisal and total entropy, but not single step entropy, were significant predictors of reading times in different parts of the sentence. This suggests that a complete model of sentence processing should incorporate both entropy and surprisal.