Datasets:
metadata
paperswithcode_id: reddit-tifu
Dataset Card for "reddit_tifu"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://github.com/ctr4si/MMN
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 1279.08 MB
- Size of the generated dataset: 219.12 MB
- Total amount of disk used: 1498.20 MB
Dataset Summary
Reddit dataset, where TIFU denotes the name of subbreddit /r/tifu. As defined in the publication, styel "short" uses title as summary and "long" uses tldr as summary.
Features includes:
- document: post text without tldr.
- tldr: tldr line.
- title: trimmed title without tldr.
- ups: upvotes.
- score: score.
- num_comments: number of comments.
- upvote_ratio: upvote ratio.
Supported Tasks and Leaderboards
Languages
Dataset Structure
We show detailed information for up to 5 configurations of the dataset.
Data Instances
long
- Size of downloaded dataset files: 639.54 MB
- Size of the generated dataset: 87.74 MB
- Total amount of disk used: 727.29 MB
An example of 'train' looks as follows.
short
- Size of downloaded dataset files: 639.54 MB
- Size of the generated dataset: 131.37 MB
- Total amount of disk used: 770.92 MB
An example of 'train' looks as follows.
Data Fields
The data fields are the same among all splits.
long
ups: afloat32feature.num_comments: afloat32feature.upvote_ratio: afloat32feature.score: afloat32feature.documents: astringfeature.tldr: astringfeature.title: astringfeature.
short
ups: afloat32feature.num_comments: afloat32feature.upvote_ratio: afloat32feature.score: afloat32feature.documents: astringfeature.tldr: astringfeature.title: astringfeature.
Data Splits
| name | train |
|---|---|
| long | 42139 |
| short | 79740 |
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
@misc{kim2018abstractive,
title={Abstractive Summarization of Reddit Posts with Multi-level Memory Networks},
author={Byeongchang Kim and Hyunwoo Kim and Gunhee Kim},
year={2018},
eprint={1811.00783},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Contributions
Thanks to @patrickvonplaten, @thomwolf for adding this dataset.