  Large Language Models (LLMs) and, more specifically, the Generative
Pre-Trained Transformers (GPT) can help stakeholders in climate action explore
digital knowledge bases and extract and utilize climate action knowledge in a
sustainable manner. However, LLMs are "probabilistic models of knowledge bases"
that excel at generating convincing texts but cannot be entirely relied upon
due to the probabilistic nature of the information produced. This brief report
illustrates the problem space with examples of LLM responses to some of the
questions of relevance to climate action.
