Datasets:
Tasks:
Text2Text Generation
Languages:
English
Size:
10K<n<100K
ArXiv:
Tags:
common-sense-inference
License:
Dataset Card for "event2Mind"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://uwnlp.github.io/event2mind/
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 1.24 MB
- Size of the generated dataset: 6.90 MB
- Total amount of disk used: 8.14 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
Languages
Dataset Structure
We show detailed information for up to 5 configurations of the dataset.
Data Instances
default
- 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.
default
Source
: astring
feature.Event
: astring
feature.Xintent
: astring
feature.Xemotion
: astring
feature.Otheremotion
: astring
feature.Xsent
: astring
feature.Osent
: astring
feature.
Data Splits Sample Size
name | train | validation | test |
---|---|---|---|
default | 46472 | 5401 | 5221 |
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
@inproceedings{event2Mind,
title={Event2Mind: Commonsense Inference on Events, Intents, and Reactions},
author={Hannah Rashkin and Maarten Sap and Emily Allaway and Noah A. Smith† Yejin Choi},
year={2018}
}
Contributions
Thanks to @thomwolf, @patrickvonplaten, @lewtun for adding this dataset.