Acquiring recursive structures through distributional learning

Languages differ regarding the depth, structure, and syntactic domains of recursive structures. Even within a single language, some structures allow infinite self-embedding while others are more restricted. For example, when expressing ownership relation, English allows embedding prenominal genitive -s, whereas postnominal is much How do speakers learn which specific not? The distributional learning proposal suggests that recursion structure (e.g., X1’s-X2) licensed if X1 position X2 productively substitutable in non-recursive input. present study tests this with an artificial language experiment. We exposed adult participants to X1-ka-X2 strings. In productive condition, almost all words attested were also position; unproductive only were. found that, as predicted, from condition likely accept unattested strings at both one- two-embedding levels than condition. Our results suggest can use information one-embedding level whether or not recursive.