A sentence in the Resultative perfect licenses two inferences: (a) the occurrence of an event (b) the state caused by this event obtains at evaluation time. In this paper I show that this use of the perfect is subject to a large number of distributional restrictions that all serve to highlight the result inference at the expense of the event inference. Nevertheless, only the event inference determines the truth conditions of this use of the perfect, the result inference being a (...) unique type of conventional implicature. I argue furthermore that, since the result state is singular, the event that causes it must also be singular, whereas the Experiential perfect is purely quantificational. But in out-of-the-blue contexts the past tense is also normally interpreted as singular. This leads to a certain amount of competition between the Resultative perfect and the past tense, and it is this competition, I suggest, that maintains the conventional (non-truth conditional) result state inference. (shrink)

Complex-transitive argument structures have received a large amount of attention from syntacticians of both formalist and cognitive-functional orientations. To account for expressions with causative resultative meanings, construction grammar has postulated a family of argument-structure constructions whose core is constituted by the Caused-Motion Construction and the Resultative Construction, exhibiting a locative complement and a predicative complement in the form of an AjP, respectively. Argument structures with NP complements, however, have been largely neglected. The present study investigates these patterns in the International (...) Corpus of English (ICE-GB) by means “collostruction analysis”. It shows that the formal distinction between AjP and NP complements corresponds to a constructional distinction hitherto unrevealed, viz. that between the Resultative Construction and another argument-structure construction, here called the “Denominative Construction”. Apart from improving existing descriptions of the network of complex-transitive argument-structure constructions, this study demonstrates that collostruction analysis can be employed in an exploratory way to discover constructions. (shrink)

Tense/aspect morphology on verbs is often thought to depend on event features like telicity, but it is not known how speakers identify these features in visual scenes. To examine this question, we asked Japanese speakers to describe computer‐generated animations of simple actions with variation in visual features related to telicity. Experiments with adults and children found that they could use goal information in the animations to select appropriate past and progressive verb forms. They also produced a large number of different (...) verb forms. To explain these findings, a deep‐learning model of verb production from visual input was created that could produce a human‐like distribution of verb forms. It was able to use visual cues to select appropriate tense/aspect morphology. The model predicted that video duration would be related to verb complexity, and past tense production would increase when it received the endpoint as input. These predictions were confirmed in a third study with Japanese adults. This work suggests that verb production could be tightly linked to visual heuristics that support the understanding of events. (shrink)