megagonlabs/arcs
ARCS ARCS (Ambiguity Resolution Corpus for SQL) is a text-to-SQL benchmark featuring naturally occurring, unconstrained ambiguities over real-world databases, with complete annotations of valid ambiguity points, interpretations, and SQL queries. gpt-6-sol achieves only 51% end-to-end execution accuracy, and no open-source model exceeds 27%. As text-to-SQL systems move beyond demonstrations toward real-world deployment, ambiguity in user questions becomes a primary source of… See the full description on the dataset page: https://huggingface.co/datasets/megagonlabs/arcs.
| Author / organization | megagonlabs |
|---|---|
| License (as declared) | cc-by-4.0 |
| Downloads | 666 (as reported by Hugging Face) |
| Likes | 2 |
| Created | 6 October 2026 |
| Last updated at source | 17 October 2026 |
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- 17 Oct 2026 Description: ARCS ARCS (Ambiguity Resolution Corpus for SQL) is a text-to-SQL benchmark featuring naturally occurring, unconstrained ambiguities over real-world databases, with complete annotations of valid ambiguity points, interpretations, and SQL que → ARCS ARCS (Ambiguity Resolution Corpus for SQL) is a text-to-SQL benchmark featuring naturally occurring, unconstrained ambiguities over real-world databases, with complete annotations of valid ambiguity points, interpretations, and SQL que
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