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A connectionist model of the retreat from verb argument structure overgeneralization*



A central question in language acquisition is how children build linguistic representations that allow them to generalize verbs from one construction to another (e.g., The boy gave a present to the girlThe boy gave the girl a present), whilst appropriately constraining those generalizations to avoid non-adultlike errors (e.g., I said no to her → *I said her no). Although a consensus is emerging that learners solve this problem using both statistical and semantics-based learning procedures (e.g., entrenchment, pre-emption, and semantic verb class formation), there currently exist few – if any – proposals for a learning model that combines these mechanisms. The present study used a connectionist model to test an account that argues for competition between constructions based on (a) verb-in construction frequency, (b) relevance of constructions for the speaker's intended message, and (c) fit between the fine-grained semantic properties of individual verbs and individual constructions. The model was able not only (a) to simulate the overall pattern of overgeneralization-then-retreat, but also (b) to use the semantics of novel verbs to predict their argument structure privileges (just as real learners do), and (c) to predict the pattern of by-verb grammaticality judgements observed in adult studies.


Corresponding author

Address for correspondence: Ben Ambridge, School of Psychology, University of Liverpool, Eleanor Rathbone Building, Bedford St South, Liverpool, L69 7ZA. e-mail:


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This research was funded by a Leverhulme Trust grant (Grant RPG-158) to Ben Ambridge and an Economic and Social Research Council Doctoral Training Centre +3 (PhD) award to Ryan Blything. <>. Account code: ES/J500094/1. Ben Ambridge is a Reader in the International Centre for Language and Communicative Development (LuCiD) at the University of Liverpool. The support of the Economic and Social Research Council (ES/L008955/1) is gratefully acknowledged.



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