Eye-tracking Evidence for Integration Cost Effects in Corpus Data

We tested the predictions of Dependency Locality Theory (DLT), a theory of linguistic processing complexity, against reading time data extracted from a large eye-tracking corpus. DLT predicts differences in processing complexity for subject and object relative clauses. We found elevated reading times on two distinct regions of these relative clauses, in line with the complexity effects predicted by DLT. We also found that transitional probability has an effect on reading time in these two regions, independent of the DLT effect. We argue our approach provides an important new way of testing sentence processing theories by evaluating them against reading data obtained from an eye-tracking corpus of naturally occurring text.