README.md

metadata

annotations_creators:
  - crowdsourced
language_creators:
  - found
language:
  - en
license:
  - cc-by-4.0
multilinguality:
  - monolingual
paperswithcode_id: null
pretty_name: WikiTableQuestions-wtq
size_categories:
  - 10K<n<100K
source_datasets:
  - wikitablequestions
task_categories:
  - question-answering
task_ids: []
tags:
  - table-question-answering

Dataset Card for WikiTableQuestions-wtq

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information

Dataset Description

• Homepage: WikiTableQuestions homepage
• Repository: WikiTableQuestions repository
• Paper: Compositional Semantic Parsing on Semi-Structured Tables
• Leaderboard: WikiTableQuestions leaderboard on PaperWithCode
• Point of Contact: [Needs More Information]

Dataset Summary

The WikiTableQuestions-wtq dataset is a small-scale dataset for the task of question answering on semi-structured tables.

This data includes the aggregation_label and answer_coordinates to make it easy to train this model on any TAPAS based modles.

Supported Tasks and Leaderboards

question-answering, table-question-answering

Languages

en

Dataset Structure

Data Instances

default

• Size of downloaded dataset files: 27.91 MB
• Size of the generated dataset: 45.68 MB
• Total amount of disk used: 73.60 MB

An example of 'validation' looks as follows:

{
  "id": "nt-0",
  "question": "What is the total average attendance at all USL First Division matches?",
  "answers": [
    "36755"
  ],
  "table": {
    "header": [
      "Year",
      "Division",
      "League",
      "Regular Season",
      "Playoffs",
      "Open Cup",
      "Avg. Attendance"
    ],
    "rows": [
      [
        "2001",
        "2",
        "USL A-League",
        "4th, Western",
        "Quarterfinals",
        "Did not qualify",
        "7,169"
      ],
      ...
    ],
    "name": "csv/204-csv/590.tsv"
  },
  "aggregation_label": "SUM",
  "answer_coordinates": [
    [
      4,
      6
    ],
    ...
  ]
}

Data Fields

The data fields are the same among all splits.

default

• id: a string feature.
• question: a string feature.
• answers: a list of string feature.
• answers_coordinates: a list of int,int tuples.
• aggregation_label: a string feature.
• table: a dictionary feature containing:
  • header: a list of string features.
  • rows: a list of list of string features:
  • name: a string feature.

Data Splits

TBA

Dataset Creation

Curation Rationale

[Needs More Information]

Source Data

Initial Data Collection and Normalization

[Needs More Information]

Who are the source language producers?

[Needs More Information]

Annotations

Annotation process

[Needs More Information]

Who are the annotators?

[Needs More Information]

Personal and Sensitive Information

[Needs More Information]

Considerations for Using the Data

Social Impact of Dataset

[Needs More Information]

Discussion of Biases

[Needs More Information]

Other Known Limitations

[Needs More Information]

Additional Information

Dataset Curators

Panupong Pasupat and Percy Liang

Licensing Information

Creative Commons Attribution Share Alike 4.0 International

Citation Information

@inproceedings{pasupat-liang-2015-compositional,
    title = "Compositional Semantic Parsing on Semi-Structured Tables",
    author = "Pasupat, Panupong and Liang, Percy",
    booktitle = "Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
    month = jul,
    year = "2015",
    address = "Beijing, China",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/P15-1142",
    doi = "10.3115/v1/P15-1142",
    pages = "1470--1480",
}

Contributions

Thanks to @SivilTaram for adding this dataset.