Datasets:
wikisql

Languages: en

Dataset Card for "wikisql"

Dataset Summary

A large crowd-sourced dataset for developing natural language interfaces for relational databases

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

We show detailed information for up to 5 configurations of the dataset.

Data Instances

default

  • Size of downloaded dataset files: 24.95 MB
  • Size of the generated dataset: 147.57 MB
  • Total amount of disk used: 172.52 MB

An example of 'validation' looks as follows.

This example was too long and was cropped:

{
    "phase": 1,
    "question": "How would you answer a second test question?",
    "sql": {
        "agg": 0,
        "conds": {
            "column_index": [2],
            "condition": ["Some Entity"],
            "operator_index": [0]
        },
        "human_readable": "SELECT Header1 FROM table WHERE Another Header = Some Entity",
        "sel": 0
    },
    "table": "{\"caption\": \"L\", \"header\": [\"Header1\", \"Header 2\", \"Another Header\"], \"id\": \"1-10015132-9\", \"name\": \"table_10015132_11\", \"page_i..."
}

Data Fields

The data fields are the same among all splits.

default

  • phase: a int32 feature.
  • question: a string feature.
  • header: a list of string features.
  • page_title: a string feature.
  • page_id: a string feature.
  • types: a list of string features.
  • id: a string feature.
  • section_title: a string feature.
  • caption: a string feature.
  • rows: a dictionary feature containing:
    • feature: a string feature.
  • name: a string feature.
  • human_readable: a string feature.
  • sel: a int32 feature.
  • agg: a int32 feature.
  • conds: a dictionary feature containing:
    • column_index: a int32 feature.
    • operator_index: a int32 feature.
    • condition: a string feature.

Data Splits

name train validation test
default 56355 8421 15878

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

@article{zhongSeq2SQL2017,
  author    = {Victor Zhong and
               Caiming Xiong and
               Richard Socher},
  title     = {Seq2SQL: Generating Structured Queries from Natural Language using
               Reinforcement Learning},
  journal   = {CoRR},
  volume    = {abs/1709.00103},
  year      = {2017}
}

Contributions

Thanks to @lewtun, @ghomasHudson, @thomwolf for adding this dataset.

Models trained or fine-tuned on wikisql