Figure out what’s going on down here – what has happened to the other soldiers? Where have all the officers gone? What diabolical nightmare lurks underneath this hellscape? Unravel the mysteries of the Bunker and get to know the nooks and crannies of this cruel sandbox to up your odds of survival. You must explore and experiment to make your way out. Solve things your own way in a semi-open world. Every decision will change the outcome of how the game responds. Hunted by an ever-present threat reacting to your every move and sound, you must adapt your play-style to face hell. With randomization and unpredictable behavior, no play-through is the same. In the shoes of the French soldier Henri Clément, you are armed with a revolver gun, a noisy dynamo flashlight, and other scarce supplies to scavenge and craft along the way. Immerse yourself in the multiple ways of tackling survival. Keep the lights on at all costs, persevere, and make your way out alive. Left all alone in a desolate WW1 bunker with only one bullet remaining in the barrel, it’s up to you to face the oppressing terrors in the dark. We believe that BIRD will contribute to advancing real-worldĪpplications of text-to-SQL research.Amnesia: The Bunker is a first-person horror game from the makers of SOMA and Amnesia. Offer insights into generating text-to-efficient-SQLs that are beneficial to Besides, we also provide an efficiency analysis to ChatGPT, only achieves 40.08% in executionĪccuracy, which is still far from the human result of 92.96%, proving thatĬhallenges still stand. Furthermore, even the mostĮffective text-to-SQL models, i.e.
Generating accurate text-to-SQLs for big databases.
TheĮxperimental results demonstrate the significance of database values in Must feature database value comprehension in addition to semantic parsing. To solve these problems, text-to-SQL models Highlights the new challenges of dirty database contents, external knowledgeīetween NL questions and database contents, and SQL efficiency, particularly in
Of 33.4 GB, spanning 37 professional domains. To mitigate this gap, we presentīird, a big benchmark for large-scale database grounded in text-to-SQL tasks,Ĭontaining 12,751 pairs of text-to-SQL data and 95 databases with a total size However, most of the prevalent benchmarks, i.e., Spider, and WikiSQL, focus onĭatabase schema with few rows of database contents leaving the gap betweenĪcademic study and real-world applications. Particular, Codex and ChatGPT have shown impressive results in this task. Into executable SQLs, has gained increasing attention in recent years. Download a PDF of the paper titled Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs, by Jinyang Li and 17 other authors Download PDF Abstract: Text-to-SQL parsing, which aims at converting natural language instructions
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