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---
configs:
- config_name: default
data_files:
- split: train
path:
- "bc-train/bc-*.jsonl.gz"
- split: validation
path:
- "bc-validation/bc-*.jsonl.gz"
- config_name: bc-clean
data_files:
- split: train
path:
- "bc-train/bc*.jsonl.gz"
- "bc-deduped/bc*.jsonl.gz"
- split: validation
path:
- "bc-validation/bc*.jsonl.gz"
- config_name: c4-en
data_files:
- split: train
path:
- "c4-en/c4-train*.json.gz"
---
# 🫘🧮 BeanCounter - Descriptive Sentences
## Dataset Summary
`BeanCounter - Descriptive Sentences` consists of sentences extracted from the BeanCounter ([🤗 Datasets](https://huggingface.co/datasets/blevy41/BeanCounter), [Paper](https://arxiv.org/abs/2409.17827)) and C4 ([🤗 Datasets](https://huggingface.co/datasets/allenai/c4), [Paper](https://arxiv.org/pdf/2104.08758)) datasets where each sentence contains at least one demographic descriptor from one of the five axes: Gender and Sex, Sexual Orientation, Nationality, Race and Ethnicity and Religion. The descriptors and axes are taken from [HolisticBias](https://aclanthology.org/2022.emnlp-main.625/). Full details of how these sentences were collected can be found in Section 3 of [Wang and Levy (2024)](https://arxiv.org/abs/2409.17827).
We include three configurations of the dataset: `bc-clean`, `default`, and `c4-en`. These consist of:
- `bc-clean`: 27.0M sentences from the `clean` subset of BeanCounter
- `default`: 19.5M sentences from the `default` subset of BeanCounter (referred to as the "final" split in the paper)
- `c4-en`: 132M sentences from the `en` subset of C4
## How can I use this?
### License
The dataset is provided under the [ODC-By](https://opendatacommons.org/licenses/by/1-0/) license. Cite our work as:
```text
@inproceedings{
wang2024beancounter,
title={BeanCounter: A low-toxicity, large-scale, and open dataset of business-oriented text},
author={Siyan Wang and Bradford Levy},
booktitle={The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
year={2024},
url={https://openreview.net/forum?id=HV5JhUZGpP}
}
```
### In 🤗 Datasets
To load the `bc-clean` subset in Datasets, one can run:
```python
from datasets import load_dataset
desc_sents = load_dataset(
"blevy41/BeanCounter",
name="bc-clean",
)
# Print out split info
print(desc_sents, "\n")
# Inspect an observation
print(f"COLUMNS IN DATA: {','.join(desc_sents['train'][1000].keys())}\n")
print(f"EXCERPT: \n\n{desc_sents['train'][1000]['sentence'][:1000]}")
```
### Datasheets for Datasets
Please refer to the original datasets for full details of their creation.
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