A large crowd-sourced dataset for developing natural language interfaces for relational databases. WikiSQL is the dataset released along with our work Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning. Regarding tokenization and Stanza, when WikiSQL was written 3-years ago, it relied on Stanza, a CoreNLP python wrapper that has since been deprecated. If you'd still like to use the tokenizer, please use the docker image. We do not anticipate switching to the current Stanza as changes to the tokenizer would render the previous results not reproducible.
Features
- Both the evaluation script as well as the dataset are stored within the repo
- Only Python 3 is supported at the moment
- Inside the data folder you will find the files in jsonl and db format
- We supply a sample predictions file for the dev set
- In addition to the raw data dump, we also release an optional annotation script that annotates WikiSQL
- Develop natural language interfaces for relational databases
Project Samples
Categories
HTML/XHTML, Database, Reinforcement Learning Frameworks, Reinforcement Learning Libraries, Reinforcement Learning AlgorithmsLicense
BSD LicenseFollow WikiSQL
You Might Also Like
Gen AI apps are built with MongoDB Atlas
MongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of WikiSQL!