Paper

Tiers, Paths, and Syntactic Locality: The View from Learning

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Abstract

Many long-distance linguistic dependencies across domains can be modeled as tier-based strictly local (TSL) patterns (Graf 2022a). Such patterns are in principle efficiently learnable, but known algorithms require unrealistic conditions. Heuser et al. (2024) present an algorithm for learning syntactic islands which involves memorizing local bigrams along attested paths; no tiers are involved. I propose a method for inferring tier membership which augments the latter algorithm to produce a TSL grammar, and show that this model also derives a version of the Height-Locality Connection (Keine 2019).

Keywords: syntax, locality, tier-based strictly local grammars, movement paths, Tolerance Principle

How to Cite:

Hanson, K., (2024) “Tiers, Paths, and Syntactic Locality: The View from Learning”, Society for Computation in Linguistics 7(1), 107–116. doi: https://doi.org/10.7275/scil.2135