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---
dataset_info:
- config_name: cc-by
features:
- name: id
dtype: string
- name: idx
dtype: int64
- name: paragraph
dtype: string
splits:
- name: train
num_bytes: 151115318
num_examples: 139463
download_size: 76199216
dataset_size: 151115318
- config_name: cc-by-nc
features:
- name: id
dtype: string
- name: idx
dtype: int64
- name: paragraph
dtype: string
splits:
- name: train
num_bytes: 78538396
num_examples: 69457
download_size: 39741294
dataset_size: 78538396
configs:
- config_name: cc-by
data_files:
- split: train
path: cc-by/train-*
- config_name: cc-by-nc
data_files:
- split: train
path: cc-by-nc/train-*
---
# ChemRxiv Paragraphs
This dataset consists of paragraphs from ChemRxiv papers with **CC BY 4.0** and **CC BY-NC 4.0** licenses, sourced from the [BASF-AI/ChemRxiv-Papers](https://huggingface.co/datasets/BASF-AI/ChemRxiv-Papers) dataset. Paragraphs are extracted using [Grobid](https://github.com/kermitt2/grobid), and filtered using an average log word probability method similar to the approach in [allenai/peS2o](https://huggingface.co/datasets/allenai/peS2o). Paragraphs with fewer than 50 words are excluded.
The number of unique papers in each license category is as follows:
- **CC BY 4.0:** 5,848 papers
- **CC BY-NC 4.0:** 3,082 papers
To obtain metadata for each paper, join on the `id` column with the [BASF-AI/ChemRxiv-Papers](https://huggingface.co/datasets/BASF-AI/ChemRxiv-Papers) dataset.
To access paragraphs for a specific license, use the `name` argument as follows:
```python
import datasets
cc_by = datasets.load_dataset('BASF-AI/ChemRxiv-Paragraphs', name='cc-by')
cc_by_nc = datasets.load_dataset('BASF-AI/ChemRxiv-Paragraphs', name='cc-by-nc')
``` |