@inproceedings{basil-etal-2026-ualberta,
    title = "{UA}lberta at {S}em{E}val-2026 Task 5: Disambiguating Stories via Task Decomposition",
    author = "Basil, David  and
      Cho, Junhyeon  and
      Girigowda, Chirooth  and
      Luo, Guoqing  and
      Momin, Sahir  and
      Robinson, Sevryn  and
      Shi, Ning  and
      Kondrak, Grzegorz",
    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-1.340/",
    pages = "2697--2708",
    ISBN = "979-8-89176-414-9",
    abstract = "We describe our system for predicting sense plausibility in short narratives. Our approach centers on task decomposition: instead of predicting a score directly, we break the problem into simpler subtasks and combine their outputs. We further improve performance by ensembling complementary signals, including word sense disambiguation and fine-tuned embedding models. We also find empirical support for the one-homonym-per-translation principle of Hauer and Kondrak (2020a). Our best ensemble system achieves competitive performance in the official evaluation. Our code and data are available on GitHub."
}