- Main
From Distributional Structure to Meaning: Learning, Syntax, and the Emergence of Categorical and Graded Interpretations
Abstract
Adjectives often admit both categorical and graded interpretations, yet perceptual evidence alone typically underdetermines which interpretation is adopted during learning. We ask how learners converge on one interpretation and whether the learning task and syntactic structure play a causal role. Using novel adjectives mapped onto an arbitrary morph space with both discrete and continuous variance, we manipulate learning task (Classification vs. Comparison) and test generalization across syntactic frames in English and Mandarin. Learning task systematically shifts alignment between adjectives and perceptual dimensions. This alignment effect is amplified in Mandarin, where syntax overtly distinguishes categorical from graded predication. Critically, alignments do not reconfigure across post-learning tasks: category assignments remain stable, while graded information surfaces selectively in intensifier choice. Reaction-time asymmetries reveal directional markedness, with categorical-to-graded shifts incurring greater cost than the reverse. Together, the results show that adjectival interpretation emerges from the alignment between task structure and distributional variance, with syntax conditioning the strength of that alignment.