Fritz Günther


2024

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Meaning Beyond Lexicality: Capturing Pseudoword Definitions with Language Models
Andrea Gregor de Varda | Daniele Gatti | Marco Marelli | Fritz Günther
Computational Linguistics, Volume 50, Issue 4 - December 2024

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 used as such in empirical studies. However, recent studies that show specific semantic patterns associated with 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 whether humans are able to ascribe explicit and declarative semantic content to unfamiliar word forms. In the present study, we utilized 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. Using 18 different 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.

2021

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Combining text and vision in compound semantics: Towards a cognitively plausible multimodal model
Abhijeet Gupta | Fritz Günther | Ingo Plag | Laura Kallmeyer | Stefan Conrad
Proceedings of the 17th Conference on Natural Language Processing (KONVENS 2021)