@inproceedings{gehring-etal-2026-semeval,
    title = "{S}em{E}val-2026 Task 5: Rating Plausibility of Word Senses in Ambiguous Stories through Narrative Understanding",
    author = "Gehring, Janosch  and
      Meyer, Selina  and
      Roth, Michael",
    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-1.448/",
    pages = "3691--3703",
    ISBN = "979-8-89176-414-9",
    abstract = "We introduce SemEval-2026 Task 5 on ``Rating Plausibility of Word Senses in Ambiguous Stories through Narrative Understanding''. The dataset for this task consists of 4-5 sentence English short stories. In each story, one sentence includes a lexical ambiguity and different senses are to be judged in terms of plausibility on a Likert scale. The task is intentionally constructed to be challenging by stories only providing sparse contextual cues. We give an overview of well-performing, frequent and interesting approaches used by participating systems. From a total of 175 registered participants and 27 submitted system description papers, the best system achieved an ``accuracy within standard deviation'' score of 93.3{\%}."
}