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Dataset: event2Mind 🏷
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from datasets import load_dataset dataset = load_dataset("event2Mind")


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Models trained or fine-tuned on event2Mind

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Table of Contents

Dataset Description

Dataset Summary

In Event2Mind, we explore the task of understanding stereotypical intents and reactions to events. Through crowdsourcing, we create a large corpus with 25,000 events and free-form descriptions of their intents and reactions, both of the event's subject and (potentially implied) other participants.

Supported Tasks

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Dataset Structure

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

Data Instances


  • Size of downloaded dataset files: 1.24 MB
  • Size of the generated dataset: 6.90 MB
  • Total amount of disk used: 8.14 MB

An example of 'validation' looks as follows.

    "Event": "It shrinks in the wash",
    "Osent": "1",
    "Otheremotion": "[\"upset\", \"angry\"]",
    "Source": "it_events",
    "Xemotion": "[\"none\"]",
    "Xintent": "[\"none\"]",
    "Xsent": ""

Data Fields

The data fields are the same among all splits.


  • Source: a string feature.
  • Event: a string feature.
  • Xintent: a string feature.
  • Xemotion: a string feature.
  • Otheremotion: a string feature.
  • Xsent: a string feature.
  • Osent: a string feature.

Data Splits Sample Size

name train validation test
default 46472 5401 5221

Dataset Creation

Curation Rationale

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Source Data

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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

    title={Event2Mind: Commonsense Inference on Events, Intents, and Reactions},
    author={Hannah Rashkin and Maarten Sap and Emily Allaway and Noah A. Smith† Yejin Choi},