salesforce/WikiSQL resource

Health v2 · maintenance only

Flags: archived

Adoption not part of the score

1805 stars · 333 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

WikiSQL is a large crowd-sourced annotated dataset for semantic parsing, pairing natural language questions with SQL queries over Wikipedia tables. It was released alongside the Seq2SQL paper and serves as a standard benchmark for developing natural language interfaces to relational databases.

Use cases

• train a text-to-SQL model
• benchmark semantic parsing accuracy on tables
• build a natural language interface for relational databases
• evaluate question answering over tabular data
• compare weakly supervised and supervised parsing approaches

When to choose

• you need a large annotated corpus for text-to-SQL research
• you want a standard benchmark with a public leaderboard
• you are studying natural language interfaces to databases

When to avoid

• you need a production natural language interface rather than a research dataset
• you need multi-table or complex SQL joins, since WikiSQL covers single-table queries
• you need actively maintained tooling, as the tokenizer dependencies are deprecated

Facets

dataset · maturity maintenance

nlp machine-learning parser database machine-learning databases data-science python cross-platform semantic-parsing text-to-sql benchmark-dataset question-answering seq2sql natural-language-processing

Member repositories

For agents

markdown · JSON · MCP: product_card(name="salesforce/WikiSQL")