Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
10K - 100K
License:
language: | |
- en | |
license: | |
- other | |
multilinguality: | |
- monolingual | |
size_categories: | |
- 10K<n<100K | |
task_categories: | |
- token-classification | |
task_ids: | |
- named-entity-recognition | |
pretty_name: BioCreative V CDR | |
# Dataset Card for "tner/bc5cdr" | |
## Dataset Description | |
- **Repository:** [T-NER](https://github.com/asahi417/tner) | |
- **Paper:** [https://academic.oup.com/database/article/doi/10.1093/database/baw032/2630271?login=true](https://academic.oup.com/database/article/doi/10.1093/database/baw032/2630271?login=true) | |
- **Dataset:** BioCreative V CDR | |
- **Domain:** Biomedical | |
- **Number of Entity:** 2 | |
### Dataset Summary | |
BioCreative V CDR NER dataset formatted in a part of [TNER](https://github.com/asahi417/tner) project. | |
The original dataset consists of long documents which cannot be fed on LM because of the length, so we split them into sentences to reduce their size. | |
- Entity Types: `Chemical`, `Disease` | |
## Dataset Structure | |
### Data Instances | |
An example of `train` looks as follows. | |
``` | |
{ | |
'tags': [2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0], | |
'tokens': ['Fasciculations', 'in', 'six', 'areas', 'of', 'the', 'body', 'were', 'scored', 'from', '0', 'to', '3', 'and', 'summated', 'as', 'a', 'total', 'fasciculation', 'score', '.'] | |
} | |
``` | |
### Label ID | |
The label2id dictionary can be found at [here](https://huggingface.co/datasets/tner/bc5cdr/raw/main/dataset/label.json). | |
```python | |
{ | |
"O": 0, | |
"B-Chemical": 1, | |
"B-Disease": 2, | |
"I-Disease": 3, | |
"I-Chemical": 4 | |
} | |
``` | |
### Data Splits | |
| name |train|validation|test| | |
|---------|----:|---------:|---:| | |
|bc5cdr|5228| 5330|5865| | |
### Citation Information | |
``` | |
@article{wei2016assessing, | |
title={Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task}, | |
author={Wei, Chih-Hsuan and Peng, Yifan and Leaman, Robert and Davis, Allan Peter and Mattingly, Carolyn J and Li, Jiao and Wiegers, Thomas C and Lu, Zhiyong}, | |
journal={Database}, | |
volume={2016}, | |
year={2016}, | |
publisher={Oxford Academic} | |
} | |
``` |