Datasets:
Tasks:
Summarization
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
aspect-based-summarization
conversations-summarization
multi-document-summarization
email-headline-generation
License:
Dataset Card for "aeslc"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://github.com/ryanzhumich/AESLC
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 11.10 MB
- Size of the generated dataset: 14.26 MB
- Total amount of disk used: 25.36 MB
Dataset Summary
A collection of email messages of employees in the Enron Corporation.
There are two features:
- email_body: email body text.
- subject_line: email subject text.
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: 11.10 MB
- Size of the generated dataset: 14.26 MB
- Total amount of disk used: 25.36 MB
An example of 'train' looks as follows.
{
"email_body": "B/C\n<<some doc>>\n",
"subject_line": "Service Agreement"
}
Data Fields
The data fields are the same among all splits.
default
email_body
: astring
feature.subject_line
: astring
feature.
Data Splits Sample Size
name | train | validation | test |
---|---|---|---|
default | 14436 | 1960 | 1906 |
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
@misc{zhang2019email,
title={This Email Could Save Your Life: Introducing the Task of Email Subject Line Generation},
author={Rui Zhang and Joel Tetreault},
year={2019},
eprint={1906.03497},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Contributions
Thanks to @patrickvonplaten, @thomwolf, @lewtun for adding this dataset.