Dataset:



Dataset Card for "social_i_qa"

Dataset Summary

We introduce Social IQa: Social Interaction QA, a new question-answering benchmark for testing social commonsense intelligence. Contrary to many prior benchmarks that focus on physical or taxonomic knowledge, Social IQa focuses on reasoning about people’s actions and their social implications. For example, given an action like "Jesse saw a concert" and a question like "Why did Jesse do this?", humans can easily infer that Jesse wanted "to see their favorite performer" or "to enjoy the music", and not "to see what's happening inside" or "to see if it works". The actions in Social IQa span a wide variety of social situations, and answer candidates contain both human-curated answers and adversarially-filtered machine-generated candidates. Social IQa contains over 37,000 QA pairs for evaluating models’ abilities to reason about the social implications of everyday events and situations. (Less)

Supported Tasks

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Languages

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Dataset Structure

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

Data Instances

default

  • Size of downloaded dataset files: 2.10 MB
  • Size of the generated dataset: 6.45 MB
  • Total amount of disk used: 8.55 MB

An example of 'validation' looks as follows.

{
    "answerA": "sympathetic",
    "answerB": "like a person who was unable to help",
    "answerC": "incredulous",
    "context": "Sydney walked past a homeless woman asking for change but did not have any money they could give to her. Sydney felt bad afterwards.",
    "label": "1",
    "question": "How would you describe Sydney?"
}

Data Fields

The data fields are the same among all splits.

default

  • context: a string feature.
  • question: a string feature.
  • answerA: a string feature.
  • answerB: a string feature.
  • answerC: a string feature.
  • label: a string feature.

Data Splits Sample Size

name train validation
default 33410 1954

Dataset Creation

Curation Rationale

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Source Data

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Annotations

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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

Contributions

Thanks to @bhavitvyamalik, @thomwolf, @patrickvonplaten, @lewtun for adding this dataset.

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