@inproceedings{fu-etal-2026-ynjtc,
    title = "{YNJTC} at {S}em{E}val-2026 Task 11: A Neuro-Symbolic Hybrid Pipeline for Content-Independent Syllogistic Reasoning",
    author = "Fu, Junhao  and
      He, Yun  and
      Zhao, Lina  and
      Li, Weijuan",
    editor = "Kochmar, Ekaterina  and
      Ghosh, Debanjan  and
      North, Kai  and
      Komachi, Mamoru",
    booktitle = "Proceedings of the 20th {I}nternational {W}orkshop on {S}emantic {E}valuation (2026)",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.semeval-1.54/",
    pages = "367--372",
    ISBN = "979-8-89176-414-9",
    abstract = "This paper presents a neuro-symbolic hybrid pipeline for SemEval-2026 Task 11 that addresses the content effect in syllogistic reasoning. The system converts natural-language syllogisms into formal mood-figure representations via regex parsing and LLM-powered extraction, then determines validity through symbolic table lookup against the 24 classically valid forms. The approach achieved a perfect Combined Score of 100.0 on Subtask 1 and competitive results on all four subtasks."
}