In human sentence processing, cognitive load can be defined many ways. This report considers a definition of cognitive load in terms of the total probability of structural options that have been disconfirmed at some point in a sentence: the surprisal of word w i given its prefix w 0...i-1 on a phrase-structural language model. These loads can be efficiently calculated using a probabilistic Earley parser (Stolcke, 1995) which is interpreted as generating predictions about reading time on a word-by-word basis. Under grammatical assumptions supported by corpusfrequency data, the operation of Stolcke's probabilistic Earley parser correctly predicts processing phenomena associated with garden path structural ambiguity and with the subject/object relative asymmetry.

Readers are sensitive to the fact that verbs may allow multiple subcategorization frames that differ in their probability of occurrence. Although a verbÕs overall subcategorization preferences can be described probabilistically, underlying non-random factors may determine those probabilities. One potential factor is verb semantics: Many verbs show sense differences, and a verbÕs subcategorization profile can vary by sense. Thus, although find can occur with a direct object (DO) or a sentential complement (SC), when it is used to mean ÔlocateÕ it occurs only with a DO, whereas in its ÔrealizeÕ sense it is SC-biased, but can take either frame. We used corpus analyses to identify verbs that occur with both frames, and found that their subcategorization probabilities differ by sense. Off-line sentence completions demonstrated that contexts can promote a specific sense of a verb, which subsequently influenced subcategorization probability. Finally, in a self-paced reading time experiment, verbs occurred in target sentences containing either a structurally unambiguous or ambiguous SC, following a context favoring the verbÕs DO- or SC-biased sense. Sensebiasing context influenced reading times at that, and interacted with ambiguity in the disambiguating region. Thus, readers use sense-contingent subcategorization preferences during on-line language comprehension.

Scholfield and Ricardo Russo for detailed statistical advice. We also thank Don Mitchell and the members of our Psycholinguistics Research Group (in particular Claudia Felser, Roger Hawkins, Theodoris Marinis, Leah Roberts) for comments and helpful suggestions. L1 and L2 Sentence Processing 2 To contribute to a better understanding of L2 sentence processing, the present study examines how second language (L2) learners parse temporary ambiguous sentences containing relative clauses. Results are reported from both off-line and on-line experiments with three groups of advanced learners of Greek, with Spanish, German or Russian as native language (L1), as well as results from corresponding experiments with a control group of adult native speakers of Greek. We found that despite their native-like mastery of the construction under investigation, the L2 learners showed different relative clause attachment preferences than the native speakers. Moreover, the L2 learners did not exhibit L1-based preferences in L2 Greek, as might be expected if they were directly influenced by attachment preferences from their native language. We suggest that L2 learners integrate information relevant for parsing differently from native speakers, with the L2 learners relying more on lexical cues than the native speakers and less on purely structurally-based parsing strategies. L1 and L2 Sentence Processing 3

Copyright by Roger Levy 2005 ii

Many recent models of language comprehension have stressed the role of distributional frequencies in determining the relative accessibility or ease of processing associated with a particular lexical item or sentence structure. However, there exist relatively few comprehensive analyses of structural frequencies, and little consideration has been given to the appro- priateness of using any particular set of corpus frequencies in modeling human language. We provide a comprehensive set of structural frequencies for a variety of written and spoken corpora, focusing on structures that have played a critical role in debates on normal psycholinguistics, aphasia, and child language acquisition, and compare our results with those from several recent papers to illustrate the implications and limitations of using corpus data in psycholinguistic research.

This article responds to M. C. MacDonald and M. H. Christiansen’s 2002 commentary on the capacity theory of working memory (WM) and its computational implementation, the Capacity-Constrained Collaborative Activation–based Production System (3CAPS). The authors also point out several shortcomings in MacDonald and Christiansen’s proposal for the construal of WM, arguing that at some level of description, their model is a variant of a small subset of the 3CAPS theory. The authors go on to describe how the symbolic and connectionist mechanisms within the hybrid 3CAPS architecture combine to produce a processing style that provides a good match to human sentence comprehension and other types of high-level cognition. The properties of 3CAPS are related to the development of other connectionist, symbolic, and hybrid systems. This article has the goals of (a) refuting some of MacDonald and Christiansen’s (2002) incorrect descriptions of the capacity theory of sentence comprehension as described in Just and Carpenter (1992); (b) pointing out the theoretical and empirical difficulties with MacDonald and Christiansen’s alternative approach and with their simple recurrent network (SRN) model in particular; and (c)

This article deals with gradience in human sentence processing. We review the experimental evidence for the role of experience in guiding the decisions of the sentence processor. Based on this evidence, we argue that the gradient behavior observed in the processing of certain syntactic constructions can be traced back to the amount of past experience that the processor has had with these constructions. In modeling terms, linguistic experience can be approximated using large, balanced corpora. We give an overview of corpus-based and probabilistic models in the literature that have exploited this fact, and hence are well placed to make gradient predictions about processing behavior. Finally, we discuss a number of questions regarding the relationship between gradience in sentence processing and gradient grammaticality, and come to the conclusion that these two phenomena should be treated separately in conceptual and modeling terms.

In line with recent studies we propose a model of human sentence processing that is based on Optimality Theory (OT). Rather than explaining parsing preferences through extralinguistically motivated parsing strategies or frequencies in the hearer’s linguistic environment, our model explains these preferences as the intermediate results of the incremental application of our OT grammar. In contrast to most other current OT-approaches to language processing, we use constraints from OT semantics rather than from OT syntax to explain on-line comprehension. We illustrate the workings of our model by investigating the comprehension of coordination, a phenomenon which is ill-understood from a competence perspective and sparsely investigated from a processing perspective. The psycholinguistic evidence that is currently available strongly suggests that the on-line comprehension of coordinate structures is influenced by constraints from many different information sources: pragmatics, discourse semantics, lexical semantics, and syntax. The competence / performance model we propose is able to formalize this cross-modular constraint interaction, and to yield concrete predictions with respect to both intermediate parsing preferences and ultimate interpretations.

Abstract not found

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