PROBABILISTIC CONSTRAINTS AND SYNTACTIC AMBIGUITY RESOLUTION

Natural languages contain probabilistic constraints that influence the resolution of ambiguities. Current models of sentence processing agre e that probabilistic constraints affect syntactic ambiguity resolution , but there has been little investigation of the constraints themselve s-what they are, how they differ in their effects on processing, and h ow they interact with one another. Three different types of probabilis tic constraints were investigated: ''pre-ambiguity'' plausibility info rmation, information about verb argument structure frequencies, and '' post-ambiguity'' constraints that arrive after the introduction of the ambiguity but prior to its disambiguation. Reading times for syntacti cally ambiguous sentences were compared to reading times for unambiguo us controls in three self-paced reading experiments. All three kinds o f constraints were found to be helpful, and when several constraints c onverged, ambiguity resolution was facilitated compared to when constr aints conflicted. The importance of these constraint interactions for ambiguity resolution models is discussed.