A logical model of competence and performance in the human sentence processor

This work is concerned with the way in which principled theories of syntax and modular theories of mind may participate in an incremental model of human linguistic performance. Central to current linguistic theory is the distinction between competence, what we know about language, and performance, how we use that knowledge. While current theories of grammar suggest a highly modular, abstract, language universal characterisation of linguistic competence, traditional models of performance have postulated parsing strategies based on construction-oriented, phrase-structure grammars. In contrast, we construct a principled theory of performance on the basis of cross-linguistic evidence, with the aim of shedding greater light on the relationship between grammar and processing. On the basis of Fodor's Modularity Hypothesis and a range of empirical evidence, we assume the existence of a distinct syntactic processor within the human sentence processor. We further hypothesize The Principle of Incremental Comprehension, entailing that the sentence processor strive to achieve maximal incremental comprehension as each word in a sentence is encountered. To achieve global incremental comprehension at the various levels of linguistic processing (syntactic, semantic, etc.) we therefore predict that modules operate concurrently. We then suggest that the modularity paradigm is one to be exploited whenever possible, precisely because it permits distributed processing within a particular domain, thereby improving real-time performance. This maxim of modularity, combined with the natural partitioning of syntactic information into several informationally encapsulated representation types leads us to posit four sub-modules within the syntactic processor: (1) phrase structure, (2) chain structure, (3) coreference, and (4) thematic structure. We then present several processing strategies which are claimed to be operative within the phrase structure module and demonstrate how the proposed architecture successfully accounts for a variety of empirical phenomena, across several languages, suggesting both the crosslinguistic application and possibly innate status of the model. We further argue that the processing strategies follow from the more general Principle of Incremental Comprehension. To demonstrate the operation of the proposed model, and illustrate its principled basis, we employ the Algorithm = Logic + Control paradigm of logic programming. In particular, we present a `deductive' implementation wherein each module is realised as a specialised metainterpreter which constructs its own representation with respect to the relevant principles of grammar. We then demonstrate how these interpreters may be `coroutined' so as to model the concurrency of the performance theory. Finally, we see that the implemented model successfully accounts for subsets of both English and German, without any variation of the control strategy. We take this as further support for the existence of an innate, unparameterised sentence processing mechanism, and discuss some possible implications of this conclusion. ii Acknowledgements First and foremost, I would like to thank my supervisors Elisabet Engdahl and Robin Cooper. I must especially thank Elisabet for her constant encouragement, guidance, and support | I feel very fortunate to have worked with her. I would also like to thank my two examiners, Eric Wehrli and Ronnie Cann, for their comments and suggestions. Without doubt, I owe a great debt to various colleagues within the Edinburgh academic community. In particular, thanks must go to Ian Lewin and Martin Pickering, for many helpful discussions during the course of this research. I would also like to thank Alan Black, Kathrin Cooper, Suresh Manandhar, and Mike Reape | all of whom have contributed valuable comments and discussion during my time in Edinburgh. Additionally, I must acknowledge all those members of the Department of Arti cial Intelligence, the Centre for Cognitive Science, and the Human Communication Research Centre who have contributed to one the richest environments in which to pursue this research. Finally, I would like to acknowledge the nancial support which made my study possible: an Edinburgh University Studentship, and Overseas Research Scheme Award, and a research assistantship at the Human Communication Research Centre. And last but not least, I owe a special thanks to the generosity of MFS Limited. iii