Proceedings of the Annual Meeting of the Cognitive Science Society

One of the most important questions in language sciences is concerned with argument structure acquisition. Here, wefocus the role of semantically most general verbs in argument structure bootstrapping. We propose a novel computationalframework that combines word embedding techniques with theories of semantic representation. Using graph vertex degreeas an index of semantic generality, we rank the semantic generality of verbs that appear in select five selective argumentstructures, the ditransitive, the spray/load, the conative, the causative-inchoative and the active-passive alternations (Levin,1993), from three corpora of children and their caregivers language productions (MacWhinney, 2000). We found Zipfiandistributions of vertex degrees in all three corpora, where verbs in children’s language input are semantically more re-stricted than adult-to-adult interactions. Except for the ditransitive, semantic general verbs do not take high rank in thevertex degree, suggesting that semantic generality might not play a role as important as previously argued.