Main content

Contributors:

Date created: | Last Updated:

: DOI | ARK

Creating DOI. Please wait...

Create DOI

Category: Project

Description: The advent of broad-coverage computational models of human sentence processing has made it possible to derive quantitative predictions for empirical phenomena of longstanding interest in psycholinguistics; one such case is the disambiguation difficulty in temporarily ambiguous sentences (garden-path sentences). Adequate evaluation of the accuracy of such quantitative predictions requires going beyond the classic binary distinction between "hard" and "easy" garden path sentences. It requires precise quantitative measurements of processing difficulty and statistical analyses that focus on more than just statistical significance. We evaluate how well a particular specification of surprisal theory predicts data from a self-paced reading study designed to estimate the magnitude of the disambiguation difficulty in two temporarily ambiguous sentence types (NP/Z and NP/S ambiguities). Using Bayesian analysis we conclude that our specification of surprisal theory cannot account for the observed NP/Z garden path effects. We have insufficient evidence to draw conclusions about whether it can account for the NP/S garden path effects.

Files

Loading files...

Citation

Recent Activity

Loading logs...