All Projects → jkkummerfeld → Text2sql Data

jkkummerfeld / Text2sql Data

Licence: other
A collection of datasets that pair questions with SQL queries.

Programming Languages

139335 projects - #7 most used programming language

Projects that are alternatives of or similar to Text2sql Data

A dataset of millions of news articles scraped from a curated list of data sources.
Stars: ✭ 255 (-11.15%)
Mutual labels:  dataset, database, natural-language-processing
Web Database Analytics
Web scrapping and related analytics using Python tools
Stars: ✭ 175 (-39.02%)
Mutual labels:  sql, database, natural-language-processing
A large annotated semantic parsing corpus for developing natural language interfaces.
Stars: ✭ 965 (+236.24%)
Mutual labels:  dataset, database, natural-language-processing
Bitnami Docker Mariadb
Bitnami MariaDB Docker Image
Stars: ✭ 251 (-12.54%)
Mutual labels:  sql, database
Scenic is maintained by Derek Prior, Caleb Hearth, and you, our contributors.
Stars: ✭ 2,856 (+895.12%)
Mutual labels:  sql, database
JayDeBeApi module allows you to connect from Python code to databases using Java JDBC. It provides a Python DB-API v2.0 to that database.
Stars: ✭ 247 (-13.94%)
Mutual labels:  sql, database
Bedquilt Core
A JSON document store on PostgreSQL
Stars: ✭ 256 (-10.8%)
Mutual labels:  sql, database
H2 is an embeddable RDBMS written in Java.
Stars: ✭ 3,078 (+972.47%)
Mutual labels:  sql, database
Game Datasets
🎮 A curated list of awesome game datasets, and tools to artificial intelligence in games
Stars: ✭ 261 (-9.06%)
Mutual labels:  dataset, database
Oie Resources
A curated list of Open Information Extraction (OIE) resources: papers, code, data, etc.
Stars: ✭ 283 (-1.39%)
Mutual labels:  dataset, natural-language-processing
Nodejs Bigquery
Node.js client for Google Cloud BigQuery: A fast, economical and fully-managed enterprise data warehouse for large-scale data analytics.
Stars: ✭ 268 (-6.62%)
Mutual labels:  sql, database
Federated mysql compatible proxy to elasticsearch, mongo, cassandra, big-table, google datastore
Stars: ✭ 268 (-6.62%)
Mutual labels:  sql, database
New version based on vert.x and docker
Stars: ✭ 242 (-15.68%)
Mutual labels:  sql, database
SQL Tools ( Dialect, Pagination, DDL dump, UrlParser, SqlStatementParser, WallFilter, BatchExecutor for Test) based Java. it is easy to integration into any ORM frameworks
Stars: ✭ 242 (-15.68%)
Mutual labels:  sql, database
DuckDB is an in-process SQL OLAP Database Management System
Stars: ✭ 4,014 (+1298.61%)
Mutual labels:  sql, database
ORM Model with Adapters for mysql, pg, sqlite in the Crystal Language.
Stars: ✭ 238 (-17.07%)
Mutual labels:  sql, database
A simple database toolkit for PHP
Stars: ✭ 236 (-17.77%)
Mutual labels:  sql, database
Semantic Kitti Api
SemanticKITTI API for visualizing dataset, processing data, and evaluating results.
Stars: ✭ 272 (-5.23%)
Mutual labels:  dataset, evaluation
Massive Js
A data mapper for Node.js and PostgreSQL.
Stars: ✭ 2,521 (+778.4%)
Mutual labels:  sql, database
React Agent
Client and server-side state management library
Stars: ✭ 235 (-18.12%)
Mutual labels:  sql, database


This repository contains data and code for building and evaluating systems that map sentences to SQL, developed as part of:

For a range of domains, we provide:

  • Sentences with annotated variables
  • SQL queries
  • A database schema
  • A database

These are improved forms of prior datasets and a new dataset we developed. We have separate files describing the datasets, systems, and tools.

Version Description
4 Data fixes
3 Data fixes and addition of data from Spider and WikiSQL
2 Data with fixes for variables incorrectly defined in questions
1 Data used in the ACL 2018 paper

Citing this work

If you use this data in your work, please cite our ACL paper and the appropriate original sources, and list the version number of the data. For example, in your paper you could write (using the BibTeX below):

In this work, we use version 4 of the modified SQL datasets from \citet{data-advising}, based on \citet{data-academic,data-atis-original,data-geography-original,data-atis-geography-scholar,data-imdb-yelp,data-restaurants-logic,data-restaurants-original,data-restaurants,data-spider,data-wikisql}

If you are only using one dataset, here are example citation commands:

Data Cite
Academic \citet{data-advising,data-academic}
Advising \citet{data-advising}
ATIS \citet{data-advising,data-atis-original,data-atis-geography-scholar}
Geography \citet{data-advising,data-geography-original,data-atis-geography-scholar}
Restaurants \citet{data-advising,data-restaurants-logic,data-restaurants-original,data-restaurants}
Scholar \citet{data-advising,data-atis-geography-scholar}
Spider \citet{data-advising,data-spider}
IMDB \citet{data-advising,data-imdb-yelp}
Yelp \citet{data-advising,data-imdb-yelp}
WikiSQL \citet{data-advising,data-wikisql}
  dataset   = {Advising},
  author    = {Catherine Finegan-Dollak, Jonathan K. Kummerfeld, Li Zhang, Karthik Ramanathan, Sesh Sadasivam, Rui Zhang, and Dragomir Radev},
  title     = {Improving Text-to-SQL Evaluation Methodology},
  booktitle = {Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2018},
  location  = {Melbourne, Victoria, Australia},
  pages     = {351--360},
  url       = {},

  dataset   = {IMDB and Yelp},
  author    = {Navid Yaghmazadeh, Yuepeng Wang, Isil Dillig, and Thomas Dillig},
  title     = {SQLizer: Query Synthesis from Natural Language},
  booktitle = {International Conference on Object-Oriented Programming, Systems, Languages, and Applications, ACM},
  month     = {October},
  year      = {2017},
  pages     = {63:1--63:26},
  url       = {},

  dataset   = {Academic},
  author    = {Fei Li and H. V. Jagadish},
  title     = {Constructing an Interactive Natural Language Interface for Relational Databases},
  journal   = {Proceedings of the VLDB Endowment},
  volume    = {8},
  number    = {1},
  month     = {September},
  year      = {2014},
  pages     = {73--84},
  url       = {},

  dataset   = {Scholar, and Updated ATIS and Geography},
  author    = {Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Jayant Krishnamurthy, and Luke Zettlemoyer},
  title     = {Learning a Neural Semantic Parser from User Feedback},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year      = {2017},
  pages     = {963--973},
  location  = {Vancouver, Canada},
  url       = {},

  dataset   = {ATIS, original},
  author    = {Deborah A. Dahl, Madeleine Bates, Michael Brown, William Fisher, Kate Hunicke-Smith, David Pallett, Christine Pao, Alexander Rudnicky, and Elizabeth Shriber},
  title     = {{Expanding the scope of the ATIS task: The ATIS-3 corpus}},
  journal   = {Proceedings of the workshop on Human Language Technology},
  year      = {1994},
  pages     = {43--48},
  url       = {},

  dataset   = {Geography, original},
  author    = {John M. Zelle and Raymond J. Mooney},
  title     = {Learning to Parse Database Queries Using Inductive Logic Programming},
  booktitle = {Proceedings of the Thirteenth National Conference on Artificial Intelligence - Volume 2},
  year      = {1996},
  pages     = {1050--1055},
  location  = {Portland, Oregon},
  url       = {},

  author    = {Lappoon R. Tang and Raymond J. Mooney},
  title     = {Automated Construction of Database Interfaces: Intergrating Statistical and Relational Learning for Semantic Parsing},
  booktitle = {2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora},
  year      = {2000},
  pages     = {133--141},
  location  = {Hong Kong, China},
  url       = {},

 author    = {Ana-Maria Popescu, Oren Etzioni, and Henry Kautz},
 title     = {Towards a Theory of Natural Language Interfaces to Databases},
 booktitle = {Proceedings of the 8th International Conference on Intelligent User Interfaces},
 year      = {2003},
 location  = {Miami, Florida, USA},
 pages     = {149--157},
 url       = {},

  author    = {Alessandra Giordani and Alessandro Moschitti},
  title     = {Automatic Generation and Reranking of SQL-derived Answers to NL Questions},
  booktitle = {Proceedings of the Second International Conference on Trustworthy Eternal Systems via Evolving Software, Data and Knowledge},
  year      = {2012},
  location  = {Montpellier, France},
  pages     = {59--76},
  url       = {},

  author    = {Tao Yu, Rui Zhang, Kai Yang, Michihiro Yasunaga, Dongxu Wang, Zifan Li, James Ma, Irene Li, Qingning Yao, Shanelle Roman, Zilin Zhang, and Dragomir Radev},
  title     = {Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task},
  booktitle = {Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing},
  year      = {2018},
  location  = {Brussels, Belgium},
  pages     = {3911--3921},
  url       = {},

  author    = {Victor Zhong, Caiming Xiong, and Richard Socher},
  title     = {Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning},
  year      = {2017},
  journal   = {CoRR},
  volume    = {abs/1709.00103},


We put substantial effort into fixing bugs in the datasets, but none of them are perfect. If you find a bug, please submit a pull request with a fix. We will be merging fixes into a development branch and only infrequently merging all of those changes into the master branch (at which point this page will be adjusted to note that it is a new release). This approach is intended to balance the need for clear comparisons between systems, while also improving the data.

For some ideas of issues to address, see our list of known issues.


This material is based in part upon work supported by IBM under contract 4915012629. Any opinions, findings, conclusions or recommendations expressed are those of the authors and do not necessarily reflect the views of IBM.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].