task_categories:conversational task_categories:text-classification task_ids:dialogue-generation task_ids:multi-class-classification language_creators:crowdsourced language_creators:machine-generated multilinguality:monolingual size_categories:10K<n<100K source_datasets:ProsocialDialog language:en license:cc-by-4.0 dialogue dialogue safety social norm rules-of-thumb arxiv:2205.12688 region:us
---
license: cc-by-4.0
task_categories:
- conversational
- text-classification
language:
- en
source_datasets:
- ProsocialDialog
language_creators:
- crowdsourced
- machine-generated
multilinguality:
- monolingual
pretty_name: ProsocialDialogFiltered
tags:
- dialogue
- dialogue safety
- social norm
- rules-of-thumb
size_categories:
- 10K<n<100K
task_ids:
- dialogue-generation
- multi-class-classification
---

## Dataset Summary
ProsocialDialogFiltered is a filtered version of the ProsocialDialog dataset.

Multiple versions are present:
- In train_no_casual, rows with the label "casual" have been filtered out as a starting point.
- In train_no_possibly, rows with "possibly needs caution" have been filtered out.
- In train_no_probably, rows with "probably needs caution" have been filtered out, as I found those to be largely pointless as well, leaving only "needs caution" and "needs intervention".
- In the final train dataset, rows containing multiple phrases such as "You should not" and "you should refrain from" have been filtered out. This is done in an attempt to reduce the number of refusals language models issue to the user, in order to create better, and more open models.

ProsocialDialog is a large-scale multi-turn English dialogue dataset to teach conversational agents to respond to problematic content.

**For more information on the source dataset, refer to the original official [huggingface](https://huggingface.co/datasets/allenai/prosocial-dialog) and [paper](https://arxiv.org/abs/2205.12688).**

Possible drawbacks:
- Some ending messages have been cut off. This is only of concern if you rely on the 'episode_done' indicator.

## Languages
English

## Additional Information

### Citation

```
@inproceedings{kim2022prosocialdialog,
    title={ProsocialDialog: A Prosocial Backbone for Conversational Agents},
    author={Hyunwoo Kim and Youngjae Yu and Liwei Jiang and Ximing Lu and Daniel Khashabi and Gunhee Kim and Yejin Choi and Maarten Sap},
    booktitle={EMNLP},
    year=2022
}
```