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SotA/Natural Language Processing/Text-To-SQL

Text-To-SQL

19 benchmarks424 papers

Text-to-SQL is a task in natural language processing (NLP) where the goal is to automatically generate SQL queries from natural language text. The task involves converting the text input into a structured representation and then using this representation to generate a semantically correct SQL query that can be executed on a database.

<span style="color:grey; opacity: 0.6">( Image credit: SyntaxSQLNet )</span>

Benchmarks

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

Execution Accuracy % (Dev)Execution Accuracy % (Test)Execution Accurarcy (Human)

Text-To-SQL on spider

Execution Accuracy (Test)Exact Match Accuracy (Dev)Execution Accuracy (Dev)Exact Match Accuracy (Test)

Text-To-SQL on Spider 2.0

Text-To-SQL on SParC

interaction match accuracy question match accuracy

Text-To-SQL on MMSQL

Text-To-SQL on SPIDER

Exact Match Accuracy (in Dev)Execution Accuracy (in Dev)

Text-To-SQL on KaggleDBQA

Exact Match (EM)

Text-To-SQL on SEDE

PCM-F1 (dev)PCM-F1 (test)

Text-To-SQL on SQL-Eval

Execution Accuracy

Text-To-SQL on Text-To-SQL

Text-To-SQL on 2D KITTI Cars Easy