Datasets:
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---
language:
- en
license:
- mit
multilinguality:
- monolingual
pretty_name: AESLC - Cleaned & Keyword Extracted
source_datasets:
- aeslc
tags:
- text2text generation
- email
- email generation
- enron
---
## about
- aeslc dataset but cleaned and keywords extracted to a new column
- an EDA website generated via pandas profiling [is on netlify here](https://aeslc-kw-train-eda.netlify.app/)
```
DatasetDict({
train: Dataset({
features: ['email_body', 'subject_line', 'clean_email', 'clean_email_keywords'],
num_rows: 14436
})
test: Dataset({
features: ['email_body', 'subject_line', 'clean_email', 'clean_email_keywords'],
num_rows: 1906
})
validation: Dataset({
features: ['email_body', 'subject_line', 'clean_email', 'clean_email_keywords'],
num_rows: 1960
})
})
```
## Python usage
Basic example notebook [here](https://colab.research.google.com/gist/pszemraj/18742da8db4a99e57e95824eaead285a/scratchpad.ipynb).
```python
from datasets import load_dataset
dataset = load_dataset("postbot/aeslc_kw")
```
## Citation
```
@InProceedings{zhang2019slg,
author = "Rui Zhang and Joel Tetreault",
title = "This Email Could Save Your Life: Introducing the Task of Email Subject Line Generation",
booktitle = "Proceedings of The 57th Annual Meeting of the Association for Computational Linguistics",
year = "2019",
address = "Florence, Italy"
}
``` |