To explain the phenomenon that certain English verbs resist passivization, Pinker proposed a semantic constraint on the passive in the adult grammar: The greater the extent to which a verb denotes an action where a patient is affected or acted upon, the greater the extent to which it is compatible with the passive. However, a number of comprehension and production priming studies have cast doubt upon this claim, finding no difference between highly affecting agent-patient/theme-experiencer passives and non-actional experiencer theme passives. (...) The present study provides evidence that a semantic constraint is psychologically real, and is readily observed when more fine-grained independent and dependent measures are used. We conclude that a semantic constraint on the passive must be incorporated into accounts of the adult grammar. (shrink)

Journal Name: Cognitive Linguistics Issue: Ahead of print.

The question of whether humans represent grammatical knowledge as a binary condition on membership in a set of well-formed sentences, or as a probabilistic property has been the subject of debate among linguists, psychologists, and cognitive scientists for many decades. Acceptability judgments present a serious problem for both classical binary and probabilistic theories of grammaticality. These judgements are gradient in nature, and so cannot be directly accommodated in a binary formal grammar. However, it is also not possible to simply reduce (...) acceptability to probability. The acceptability of a sentence is not the same as the likelihood of its occurrence, which is, in part, determined by factors like sentence length and lexical frequency. In this paper, we present the results of a set of large-scale experiments using crowd-sourced acceptability judgments that demonstrate gradience to be a pervasive feature in acceptability judgments. We then show how one can predict acceptability judgments on the basis of probability by augmenting probabilistic language models with an acceptability measure. This is a function that normalizes probability values to eliminate the confounding factors of length and lexical frequency. We describe a sequence of modeling experiments with unsupervised language models drawn from state-of-the-art machine learning methods in natural language processing. Several of these models achieve very encouraging levels of accuracy in the acceptability prediction task, as measured by the correlation between the acceptability measure scores and mean human acceptability values. We consider the relevance of these results to the debate on the nature of grammatical competence, and we argue that they support the view that linguistic knowledge can be intrinsically probabilistic. (shrink)

An experimental study was conducted on children aged 2;6–3;0 and 3;6–4;0 investigating the priming effect of two WANT-constructions to establish whether constructional competition contributes to English-speaking children's infinitival to omission errors. In two between-participant groups, children either just heard or heard and repeated WANT-to, WANT-X, and control prime sentences after which to-infinitival constructions were elicited. We found that both age groups were primed, but in different ways. In the 2;6–3;0 year olds, WANT-to primes facilitated the provision of to in target (...) utterances relative to the control contexts, but no significant effect was found for WANT-X primes. In the 3;6–4;0 year olds, both WANT-to and WANT-X primes showed a priming effect, namely WANT-to primes facilitated and WANT-X primes inhibited provision of to. We argue that these effects reflect developmental differences in the level of proficiency in and preference for the two constructions, and they are broadly consistent with “priming as implicit learning” accounts. The current study shows that children as young as 2;6–3;0 years of age can be primed when they have only heard particular constructions, children are acquiring at least two constructions for the matrix verb WANT, and that these two WANT-constructions compete for production. (shrink)