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CLARITY framework tackles ambiguity in conversational NL2SQL systems

By PulseAugur Editorial · [2 sources] ·

Researchers have developed CLARITY, a new framework and benchmark designed to evaluate Natural Language to SQL (NL2SQL) systems' ability to handle ambiguous and unanswerable queries in interactive settings. Unlike previous benchmarks, CLARITY generates complex ambiguities and simulates diverse user interactions across multiple turns. Evaluations on existing datasets like Spider and BIRD revealed that current leading NL2SQL systems, even those powered by large language models, experience significant performance drops when faced with these multifaceted ambiguities, often failing to pinpoint the exact source of the issue. AI

IMPACT Highlights critical limitations in current NL2SQL systems, driving the need for improved ambiguity handling in real-world applications.

RANK_REASON Academic paper introducing a new framework and benchmark for evaluating NL2SQL systems.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

CLARITY framework tackles ambiguity in conversational NL2SQL systems

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Academic paper introducing a new framework and benchmark for evaluating NL2SQL systems.
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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Tabinda Sarwar, Farhad Moghimifar, Cong Duy Vu Hoang, Xiaoxiao Ma, Shawn Chang Xu, Fahimeh Saleh, Poorya Zaremoodi, Avirup Sil, Katrin Kirchhoff ·

    CLARITY: A Framework and Benchmark for Conversational Language Ambiguity and Unanswerability in Interactive NL2SQL Systems

    arXiv:2604.22313v1 Announce Type: new Abstract: NL2SQL systems deployed in industry settings often encounter ambiguous or unanswerable queries, particularly in interactive scenarios with incomplete user clarification. Existing benchmarks typically assume a single source of ambigu…

  2. arXiv cs.CL TIER_1 English(EN) · Katrin Kirchhoff ·

    CLARITY: A Framework and Benchmark for Conversational Language Ambiguity and Unanswerability in Interactive NL2SQL Systems

    NL2SQL systems deployed in industry settings often encounter ambiguous or unanswerable queries, particularly in interactive scenarios with incomplete user clarification. Existing benchmarks typically assume a single source of ambiguity and rely on user interaction for resolution,…

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