Contextualising (Im)plausible Events Triggers Figurative Language
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Abstract (arXiv)
This work explores the connection between (non-)literalness and plausibility at the example of subject-verb-object events in English. We design a systematic setup of plausible and implausible event triples in combination with abstract and concrete constituent categories. Our analysis of human and LLM-generated judgments and example contexts reveals substantial differences between assessments of plausibility. While humans excel at nuanced detection and contextualization of (non-)literal vs. implausible events, LLM results reveal only shallow contextualization patterns with a bias to trade implausibility for non-literal, plausible interpretations.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 24 references that are in the map. First posted on arXiv 9 Apr 2026.
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References · 6
- 2024The Llama 3 Herd of Modelscited by 14,192
- 2018Modeling Semantic Plausibility by Injecting World Knowledgecited by 24
- 2024Log Probabilities Are a Reliable Estimate of Semantic Plausibility in Base and Instruction-Tuned Language Modelscited by 24
- 2021Modeling Event Plausibility with Consistent Conceptual Abstractioncited by 20
- 2019Can a Gorilla Ride a Camel? Learning Semantic Plausibility from Textcited by 9
- 2024A Dataset for Physical and Abstract Plausibility and Sources of Human Disagreementcited by 3
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