@inproceedings{sawinski-2026-factuep,
    title = "{F}act{UEP} at {S}em{E}val-2026 Task 4: Structured Narrative Similarity Scoring with Aspect Decomposition and Weak-Signal Gating",
    author = "Sawinski, Marcin",
    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-1.147/",
    pages = "1075--1088",
    ISBN = "979-8-89176-414-9",
    abstract = "This paper presents approach to narrative similarity prediction for SemEval-2026 Task 4 Track A. We introduce an LLM-based system that operationalizes the three core dimensions{---}Abstract Theme, Course of Action, and Outcomes{---}via schema-constrained prompting to enforce structured outputs and alignment with the annotation protocol. The system proceeds in three stages: structured aspect decomposition and scoring, weak-signal gating for low-confidence cases, and a targeted LLM-based tiebreak. The final model achieved near-human performance and ranked second on the Track A leaderboard."
}