Dependencies and Hierarchical Structure in Sentence Processing

In memory-based models of human sentence processing it is assumed that the completion of a dependency between a syntactic head and its dependents is a major source of processing difficulty in non-ambiguous sentences, and that this integration cost is a function of the distance between the two elements. However, it remains open how to measure the distance between two dependent elements. While many current models employ a linear distance measure, we instead propose to measure the distance between a head and its dependents as the path in the phrase structure tree connecting the two elements. We evaluate this structural distance as a measure of dependency integration and show that it is a better predictor of human reading times than other measures. Moreover, we find that evaluated on reading data from naturally occurring texts, dependency integration is not actually a cost, as higher dependency integration distances led to lower reading times.