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Datasets/BIRD (BIg Bench for LaRge-scale Database Grounded Text-to-SQL Evaluation)

BIRD (BIg Bench for LaRge-scale Database Grounded Text-to-SQL Evaluation)

Introduced 2023-05-04

BIRD (BIg Bench for LaRge-scale Database Grounded Text-to-SQL Evaluation) represents a pioneering, cross-domain dataset that examines the impact of extensive database contents on text-to-SQL parsing. BIRD contains over 12,751 unique question-SQL pairs and 95 big databases with a total size of 33.4 GB. It also covers more than 37 professional domains, such as blockchain, hockey, healthcare and education, etc.

Benchmarks

Semantic Parsing/Execution Accuracy % (Test)Semantic Parsing/Execution Accuracy % (Dev)Semantic Parsing/Execution Accurarcy (Human)Text-To-SQL/Execution Accuracy % (Test)Text-To-SQL/Execution Accuracy % (Dev)Text-To-SQL/Execution Accurarcy (Human)

Related Benchmarks

BIRDSAI - ICVGIP 2020/Object Tracking/AnimalsBIRDSAI - ICVGIP 2020/Object Tracking/HumansBird-225/Fine-Grained Image Classification/AccuracyBird-225/Image Classification/AccuracyBirdCLEF 2021/Audio Classification/AccuracyBirdCLEF 2021/Classification/AccuracyBirdClef 2020 (Pruned)/Few-Shot Learning/Top-1 Accuracy(5-Way-1-Shot)BirdClef 2020 (Pruned)/Meta-Learning/Top-1 Accuracy(5-Way-1-Shot)Birdsnap/Fine-Grained Image Classification/AccuracyBirdsnap/Image Classification/AccuracyBirdsnap/Image Clustering/Accuracy

Statistics

Papers
15
Benchmarks
6

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Tasks

Semantic ParsingText-To-SQL