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DOI: 10.4230/LIPIcs.TIME.2025.18

Prompting LLMs for the Run-Time Event Calculus (Short Paper)

Authors: Andreas Kouvaras, Periklis Mantenoglou, and Alexander Artikis

Published in: LIPIcs, Volume 355, 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)

Abstract

Composite activity recognition systems analyse streams of low-level, symbolic events to identify instances of complex activities based on their formal definitions. Crafting these definitions is a challenging task, as it often requires specifying intricate spatio-temporal constraints, and acquiring labeled data for automated learning is difficult. To address this challenge, we introduce a method that leverages pre-trained Large Language Models (LLMs) to generate composite activity definitions, in the language of the Run-Time Event Calculus, from natural language descriptions.

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Andreas Kouvaras, Periklis Mantenoglou, and Alexander Artikis. Prompting LLMs for the Run-Time Event Calculus (Short Paper). In 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 355, pp. 18:1-18:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{kouvaras_et_al:LIPIcs.TIME.2025.18,
  author =	{Kouvaras, Andreas and Mantenoglou, Periklis and Artikis, Alexander},
  title =	{{Prompting LLMs for the Run-Time Event Calculus}},
  booktitle =	{32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)},
  pages =	{18:1--18:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-401-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{355},
  editor =	{Vidal, Thierry and Wa{\l}\k{e}ga, Przemys{\l}aw Andrzej},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2025.18},
  URN =		{urn:nbn:de:0030-drops-244641},
  doi =		{10.4230/LIPIcs.TIME.2025.18},
  annote =	{Keywords: Event Calculus, temporal pattern matching, composite event recognition}
}

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Prompting LLMs for the Run-Time Event Calculus (Short Paper)

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