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 girl" ? "The 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.