social_i_qa / README.md
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metadata
language:
  - en
paperswithcode_id: social-iqa
pretty_name: Social Interaction QA
dataset_info:
  features:
    - name: context
      dtype: string
    - name: question
      dtype: string
    - name: answerA
      dtype: string
    - name: answerB
      dtype: string
    - name: answerC
      dtype: string
    - name: label
      dtype: string
  splits:
    - name: train
      num_bytes: 6389954
      num_examples: 33410
    - name: validation
      num_bytes: 376508
      num_examples: 1954
  download_size: 2198056
  dataset_size: 6766462

Dataset Card for "social_i_qa"

Table of Contents

Dataset Description

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 and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

  • Size of downloaded dataset files: 2.20 MB
  • Size of the generated dataset: 6.76 MB
  • Total amount of disk used: 8.97 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

name train validation
default 33410 1954

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

More Information Needed

Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

More Information Needed

Citation Information


Contributions

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