metadata
license: cc0-1.0
NCBI Disease Corpus for Binary Sequence Classification
Description
This dataset is part of the MSc dissertation study titled 'Investigating the Potential of Identifying Kidney Disease-Related Articles Using Transformer Models and Large Language Models' at the University of Southampton. It is a modified version of the NCBI Disease Corpus, with a binary label added to each sample. The binary label indicates whether the sample contains disease concepts (Class 1) or not (Class 0).
Dataset Structure
The dataset is split into train and test sets:
| Class 1 | Class 0 | Total Samples per Split | |
| Train | 3,419 | 2,938 | 6,357 |
| Test | 539 | 402 | 941 |
Columns:
- id: Unique identifier for each sample. The ID indicate the original index of the sample in the NCBI Disease Corpus. For example, 'test-0' indicates the first sample in the test set.
- tokens: The text content of the sample split into tokens.
- ner_tags: The named entity recognition (NER) tags for each token. The tags are 0, 1, and 2. 0 indicates that the token is not part of a disease concept, 1 indicates the beginning of a disease concept, and 2 indicates the continuation of a disease concept.
- Text: The joined text content of the sample.
- labels: The binary label for the sample. 1 indicates that the sample contains disease concepts, and 0 indicates that the sample does not contain disease concepts.