README.md

metadata

annotations_creators:
  - crowdsourced
language:
  - en
language_creators:
  - found
license:
  - unknown
multilinguality:
  - monolingual
pretty_name: Event2Mind
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - text2text-generation
task_ids: []
paperswithcode_id: event2mind
tags:
  - common-sense-inference
dataset_info:
  features:
    - name: Source
      dtype: string
    - name: Event
      dtype: string
    - name: Xintent
      dtype: string
    - name: Xemotion
      dtype: string
    - name: Otheremotion
      dtype: string
    - name: Xsent
      dtype: string
    - name: Osent
      dtype: string
  splits:
    - name: test
      num_bytes: 649273
      num_examples: 5221
    - name: train
      num_bytes: 5916384
      num_examples: 46472
    - name: validation
      num_bytes: 672365
      num_examples: 5401
  download_size: 1300770
  dataset_size: 7238022

Dataset Card for "event2Mind"

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • 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
  • Contributions

Dataset Description

• Homepage: https://uwnlp.github.io/event2mind/
• Repository: https://github.com/uwnlp/event2mind
• Paper: Event2Mind: Commonsense Inference on Events, Intents, and Reactions
• Point of Contact: Hannah Rashkin, Maarten Sap
• Size of downloaded dataset files: 1.30 MB
• Size of the generated dataset: 7.24 MB
• Total amount of disk used: 8.54 MB

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 and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

• Size of downloaded dataset files: 1.30 MB
• Size of the generated dataset: 7.24 MB
• Total amount of disk used: 8.54 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.

default

• 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

name	train	validation	test
default	46472	5401	5221

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

@inproceedings{rashkin-etal-2018-event2mind,
    title = "{E}vent2{M}ind: Commonsense Inference on Events, Intents, and Reactions",
    author = "Rashkin, Hannah  and
      Sap, Maarten  and
      Allaway, Emily  and
      Smith, Noah A.  and
      Choi, Yejin",
    booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2018",
    address = "Melbourne, Australia",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/P18-1043",
    doi = "10.18653/v1/P18-1043",
    pages = "463--473",
}

Contributions

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