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Uncertainty and Expectation in Sentence Processing: Evidence From Subcategorization Distributions
Author(s) -
Linzen Tal,
Jaeger T. Florian
Publication year - 2016
Publication title -
cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.498
H-Index - 114
eISSN - 1551-6709
pISSN - 0364-0213
DOI - 10.1111/cogs.12274
Subject(s) - sentence processing , sentence , verb , subcategorization , complement (music) , natural language processing , reading (process) , computer science , comprehension , artificial intelligence , affect (linguistics) , linguistics , psychology , communication , biochemistry , chemistry , philosophy , complementation , programming language , gene , phenotype
Abstract There is now considerable evidence that human sentence processing is expectation based: As people read a sentence, they use their statistical experience with their language to generate predictions about upcoming syntactic structure. This study examines how sentence processing is affected by readers' uncertainty about those expectations. In a self‐paced reading study, we use lexical subcategorization distributions to factorially manipulate both the strength of expectations and the uncertainty about them. We compare two types of uncertainty: uncertainty about the verb's complement, reflecting the next prediction step; and uncertainty about the full sentence, reflecting an unbounded number of prediction steps. We find that uncertainty about the full structure, but not about the next step, was a significant predictor of processing difficulty: Greater reduction in uncertainty was correlated with increased reading times (RTs). We additionally replicated previously observed effects of expectation violation (surprisal), orthogonal to the effect of uncertainty. This suggests that both surprisal and uncertainty affect human RTs. We discuss the consequences for theories of sentence comprehension.