In this dissertation, we aimed to investigate the two competing memory-based and expectation-based accounts of sentence processing in resolving a long-distance dependency in Persian. According to memory-based account, delaying the appearance of a verb in a noun-verb dependency increases the processing difficulty at the verb; however, the expectation-based account makes the opposite prediction, that is, this delay renders the verb more predictable and therefore easier to process. We used (separable) complex predicates as the most widely-used type of verb in Persian as compared to simple verbs. In two self-paced reading and two eye-tracking experiments, we delayed the appearance of the verb by interposing a relative clause (the first self-paced reading and eye-tracking studies) or a long prepositional phrase (the second self-paced reading and eye-tracking studies). We also included a simple noun-verb predicate configuration with the same distance manipulation; here, the exact identity of the verb was not predictable (weak predictability) whereas it was strongly predictable in the complex predicate conditions, as confirmed by a pretest. Another pretest confirmed the acceptability of the separable complex predicates we used. Thus, the design crossed predictability strength and distance. The results showed that the Persian data is in favor of memory-based account and contrary to the main prediction of expectation-based account as the locality effects were seen in all the experiments. Also, there is not much evidence that strong prediction can cancel locality effects. In sum, the assumption that verb-final languages exhibit the patterns of expectation-based account is not upheld by our Persian experiments.
|Qualification||Doctor of Philosophy|
|Place of Publication||[Groningen]|
|Publication status||Published - 2017|