Dataset:
web_questions



Dataset Card for "web_questions"

Dataset Summary

This dataset consists of 6,642 question/answer pairs. The questions are supposed to be answerable by Freebase, a large knowledge graph. The questions are mostly centered around a single named entity. The questions are popular ones asked on the web (at least in 2013).

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: 1.21 MB
  • Size of the generated dataset: 0.79 MB
  • Total amount of disk used: 2.00 MB

An example of 'train' looks as follows.

{
    "answers": ["Jamaican Creole English Language", "Jamaican English"],
    "question": "what does jamaican people speak?",
    "url": "http://www.freebase.com/view/en/jamaica"
}

Data Fields

The data fields are the same among all splits.

default

  • url: a string feature.
  • question: a string feature.
  • answers: a list of string features.

Data Splits

name train test
default 3778 2032

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

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

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

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


@inproceedings{berant-etal-2013-semantic,
    title = "Semantic Parsing on {F}reebase from Question-Answer Pairs",
    author = "Berant, Jonathan  and
      Chou, Andrew  and
      Frostig, Roy  and
      Liang, Percy",
    booktitle = "Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing",
    month = oct,
    year = "2013",
    address = "Seattle, Washington, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D13-1160",
    pages = "1533--1544",
}

Contributions

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

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Models trained or fine-tuned on web_questions