Meaning Beyond Lexicality: Capturing Pseudoword Definitions with Large Language Models

Abstract

Pseudowords such as "knackets" or "spechy" – letter strings that are consistent with the orthotactical rules of a language but do not appear in its lexicon – are traditionally considered to be meaningless, and employed as such in empirical studies. However, recent studies that show specific semantic patterns associated to these words as well as semantic effects on human pseudoword processing have cast doubt on this view. While these studies suggest that pseudowords have meanings, they provide only extremely limited insight as to what these meanings are. In the present study, we employed an exploratory-confirmatory study design to examine this question. In a first exploratory study, we started from a pre-existing dataset of words and pseudowords alongside human-generated definitions for these items. Employing 18 different Large Language Models, we showed that the definitions actually produced for (pseudo)words were closer to their respective (pseudo)words than the definitions for the other items. Based on these initial results, we conducted a second, pre-registered, high-powered confirmatory study collecting a new, controlled set of (pseudo)word interpretations. This second study confirmed the results of the first one. Taken together, these findings support the idea that meaning construction is supported by a flexible form-to-meaning mapping system based on statistical regularities in the language environment that can accommodate novel lexical entries as soon as they are encountered.