Rasende Rakete at SemEval-2026 Task 6: LLM-First Approach with Iterative Prompt Repair for Classifying Evasion in Political Interviews

Omar Elbeltagui; Nils Knittel; Leonie Süß; Umut Yıldırır; Qiyan Zhai; Shaghayegh Kolli; Jana Diesner

Rasende Rakete at SemEval-2026 Task 6: LLM-First Approach with Iterative Prompt Repair for Classifying Evasion in Political Interviews

Omar Elbeltagui, Nils Knittel, Leonie Süß, Umut Yıldırır, Qiyan Zhai, Shaghayegh Kolli, Jana Diesner

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Abstract

We describe our system for SemEval-2026 Task 6 (CLARITY), which addresses automatic detection of evasive responses in political interviews. We adopt an LLM-first approach built around two core contributions: (i) an iterative prompt repair loop that diagnoses classification errors on concrete failure examples and applies prompt revisions and (ii) a configurable end-to-end Java Pipeline that supports multiple LLM providers, strategies, and systematic experimentation.

Anthology ID:: 2026.semeval-1.280
Volume:: Proceedings of the 20th International Workshop on Semantic Evaluation (2026)
Month:: July
Year:: 2026
Address:: San Diego, California, USA
Editors:: Ekaterina Kochmar, Debanjan Ghosh, Kai North, Mamoru Komachi
Venues:: SemEval | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 2216–2227
Language:
URL:: https://aclanthology.org/2026.semeval-1.280/
DOI:
Bibkey:
Cite (ACL):: Omar Elbeltagui, Nils Knittel, Leonie Süß, Umut Yıldırır, Qiyan Zhai, Shaghayegh Kolli, and Jana Diesner. 2026. Rasende Rakete at SemEval-2026 Task 6: LLM-First Approach with Iterative Prompt Repair for Classifying Evasion in Political Interviews. In Proceedings of the 20th International Workshop on Semantic Evaluation (2026), pages 2216–2227, San Diego, California, USA. Association for Computational Linguistics.
Cite (Informal):: Rasende Rakete at SemEval-2026 Task 6: LLM-First Approach with Iterative Prompt Repair for Classifying Evasion in Political Interviews (Elbeltagui et al., SemEval 2026)
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PDF:: https://aclanthology.org/2026.semeval-1.280.pdf

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@inproceedings{elbeltagui-etal-2026-rasende,
    title = "Rasende Rakete at {S}em{E}val-2026 Task 6: {LLM}-First Approach with Iterative Prompt Repair for Classifying Evasion in Political Interviews",
    author = {Elbeltagui, Omar  and
      Knittel, Nils  and
      S{\"u}{\ss}, Leonie  and
      Y{\i}ld{\i}r{\i}r, Umut  and
      Zhai, Qiyan  and
      Kolli, Shaghayegh  and
      Diesner, Jana},
    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://aclanthology.org/2026.semeval-1.280/",
    pages = "2216--2227",
    ISBN = "979-8-89176-414-9",
    abstract = "We describe our system for SemEval-2026 Task 6 (CLARITY), which addresses automatic detection of evasive responses in political interviews. We adopt an LLM-first approach built around two core contributions: (i) an iterative prompt repair loop that diagnoses classification errors on concrete failure examples and applies prompt revisions and (ii) a configurable end-to-end Java Pipeline that supports multiple LLM providers, strategies, and systematic experimentation."
}

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%0 Conference Proceedings
%T Rasende Rakete at SemEval-2026 Task 6: LLM-First Approach with Iterative Prompt Repair for Classifying Evasion in Political Interviews
%A Elbeltagui, Omar
%A Knittel, Nils
%A Süß, Leonie
%A Yıldırır, Umut
%A Zhai, Qiyan
%A Kolli, Shaghayegh
%A Diesner, Jana
%Y Kochmar, Ekaterina
%Y Ghosh, Debanjan
%Y North, Kai
%Y Komachi, Mamoru
%S Proceedings of the 20th International Workshop on Semantic Evaluation (2026)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-414-9
%F elbeltagui-etal-2026-rasende
%X We describe our system for SemEval-2026 Task 6 (CLARITY), which addresses automatic detection of evasive responses in political interviews. We adopt an LLM-first approach built around two core contributions: (i) an iterative prompt repair loop that diagnoses classification errors on concrete failure examples and applies prompt revisions and (ii) a configurable end-to-end Java Pipeline that supports multiple LLM providers, strategies, and systematic experimentation.
%U https://aclanthology.org/2026.semeval-1.280/
%P 2216-2227

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Markdown (Informal)

[Rasende Rakete at SemEval-2026 Task 6: LLM-First Approach with Iterative Prompt Repair for Classifying Evasion in Political Interviews](https://aclanthology.org/2026.semeval-1.280/) (Elbeltagui et al., SemEval 2026)

Rasende Rakete at SemEval-2026 Task 6: LLM-First Approach with Iterative Prompt Repair for Classifying Evasion in Political Interviews (Elbeltagui et al., SemEval 2026)

ACL

Omar Elbeltagui, Nils Knittel, Leonie Süß, Umut Yıldırır, Qiyan Zhai, Shaghayegh Kolli, and Jana Diesner. 2026. Rasende Rakete at SemEval-2026 Task 6: LLM-First Approach with Iterative Prompt Repair for Classifying Evasion in Political Interviews. In Proceedings of the 20th International Workshop on Semantic Evaluation (2026), pages 2216–2227, San Diego, California, USA. Association for Computational Linguistics.