Generalization via Aggregation: An Analogical Inference Mechanism for Natural Language Syntax

How do speakers of a language infer the grammatical structure of a newly heard sentence? In exemplar-based theories of language, this inference process is said to consist of comparing the novel sentence to sentences that the speaker has already heard, and making analogical generalizations from the observed partial similarities. There have been attempts at fully specifying and computationally implementing such a process, but it remains an open question whether this is a feasible approach, given the fact that even relatively short word sequences tend to occur very infrequently in corpora. In this talk, I propose a novel exemplar-based grammatical inference mechanism and present some experiments testing its feasibility.

Zoom link: https://us02web.zoom.us/j/84594385686?pwd=a7KPWoNLrPg11xNTi5Ug91YR5mHmmS.1

Az esemény weboldala és további információ: https://lps.elte.hu/lps/2025-2026/March/