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Dataset Card for "event2Mind"
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
Languages
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
: astring
feature.Event
: astring
feature.Xintent
: astring
feature.Xemotion
: astring
feature.Otheremotion
: astring
feature.Xsent
: astring
feature.Osent
: astring
feature.
Data Splits
name | train | validation | test |
---|---|---|---|
default | 46472 | 5401 | 5221 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
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{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.
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