@inproceedings{calo-etal-2026-logic,
    title = "A Logic-Based Approach to Hallucinations in Data-to-Text {NLG}: Experiments with Human and {LLM} Annotators",
    author = "Cal{\`o}, Eduardo  and
      Mahamood, Saad  and
      Gatt, Albert  and
      Van Deemter, Kees",
    editor = "Mohammad, Saif M.  and
      Ousidhoum, Nedjma",
    booktitle = "Proceedings of the 15th Joint Conference on Lexical and Computational Semantics (*{SEM} 2026)",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.starsem-conference.3/",
    pages = "28--62",
    ISBN = "979-8-89176-413-2",
    abstract = "Hallucinations are a persistent challenge in natural language generation, including data-to-text. van Deemter (2024) introduced a framework based on the relation of logical consequence ({''}follows from''), which divides all data-to-text hallucinations into seven disjoint categories. We examine whether human annotators and large language models are able to apply the framework, in two data-to-text domains. Results suggest that the framework is applicable, although there are significant domain-dependent variations, as well as discrepancies between human and model judgments. We also uncover several issues that should inform future work on hallucination."
}