Distributional learning of subcategories in an artificial grammar: Category generalization and subcategory restrictions.

There has been significant recent interest in clarifying how learners use distributional information during language acquisition. Many researchers have suggested that distributional learning mechanisms play a major role during grammatical category acquisition, since linguistic form-classes (like and ) and subclasses (like and grammatical gender) are primarily defined by the ways lexical items are distributed in syntactic contexts. Though recent experimental work has affirmed the importance of distributional information for category acquisition, there has been little evidence that learners can acquire linguistic based only on distributional cues. Across two artificial grammar-learning experiments, we demonstrate that subclasses can be acquired from distributional cues alone. These results add to a body of work demonstrating rational use of distributional information to acquire complex linguistic structures.