Do LLMs Dream of Ontologies?

• URL: http://arxiv.org/abs/2401.14931v1
• Date: Fri, 26 Jan 2024 15:10:23 GMT
• Title: Do LLMs Dream of Ontologies?
• Authors: Marco Bombieri, Paolo Fiorini, Simone Paolo Ponzetto, Marco Rospocher
• Abstract summary: Large language models (LLMs) have recently revolutionized automated text understanding and generation. This paper investigates whether and to what extent general-purpose pre-trained LLMs have information from known.
• Score: 15.049502693786698
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Large language models (LLMs) have recently revolutionized automated text understanding and generation. The performance of these models relies on the high number of parameters of the underlying neural architectures, which allows LLMs to memorize part of the vast quantity of data seen during the training. This paper investigates whether and to what extent general-purpose pre-trained LLMs have memorized information from known ontologies. Our results show that LLMs partially know ontologies: they can, and do indeed, memorize concepts from ontologies mentioned in the text, but the level of memorization of their concepts seems to vary proportionally to their popularity on the Web, the primary source of their training material. We additionally propose new metrics to estimate the degree of memorization of ontological information in LLMs by measuring the consistency of the output produced across different prompt repetitions, query languages, and degrees of determinism.

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