@inproceedings{hamano-etal-2026-ufg,
    title = "{UFG}-Semantic at {S}em{E}val-2026 Task 6: {CLARITY} - Unmasking Political Question Evasions",
    author = "Hamano, Aline  and
      Felicio, Beatriz  and
      Galv{\~a}o, Henrique  and
      Da Silva, N{\'a}dia",
    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-1.300/",
    pages = "2384--2393",
    ISBN = "979-8-89176-414-9",
    abstract = "We propose an approach for Task 6: CLARITY - Unmasking Political Question Evasions. We make use of data augmentation, supervised fine-tuning, and model benchmarking to detect and classify response ambiguity in political discourse. Building on well-founded theory on equivocation and leveraging recent advancements in language modeling, our system was structured based on question/answer (QA) pairs extracted from presidential interviews, and it was evaluated in Clarity-level Classification and Evasion-level Classification."
}