README.md

---
license: mit
task_categories:
- token-classification
task_ids:
- named-entity-recognition
dataset_info:
  features:
  - name: tokens
    list: string
  - name: tags
    list: string
  splits:
  - name: train
    num_bytes: 1761536
    num_examples: 3361
  - name: validation
    num_bytes: 900871
    num_examples: 1819
  download_size: 472719
  dataset_size: 2662407
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
---

---

# Proposed Active Learning Data split
## Overview
This dataset release represents a proposed and experimental data split(processed in BIO format) designed specifically to support and validate planned active learning (AL) cycles for biomedical Named Entity Recognition (NER).

The current version is not a final benchmark split. Instead, it serves as an initial, controlled setup for testing active learning strategies, model uncertainty sampling, 
and iterative annotation workflows prior to large-scale development.

Both splits (train and validation) have been carefully curated to ensure coverage of all three target entity types:

- **CellLine**

- **CellType**

- **Tissue**

For details on how the splits were created, please refer to raw data and documentation available [here](https://huggingface.co/datasets/OTAR3088/AL_Test_data)

This BIO format has been generated using a Biomedical transformer-based tokenizer for consistency with downstream model training. 
---

## Intended Use

### Primary Use
- Supervised NER training for biomedical NLP tasks

### Not Intended For
- Clinical or patient-level decision making