Datasets:
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---
dataset_info:
features:
- name: tokens
sequence: string
- name: tags
sequence: int64
splits:
- name: train
num_bytes: 118725876
num_examples: 88619
- name: test
num_bytes: 29511302
num_examples: 22110
download_size: 34363806
dataset_size: 148237178
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
task_categories:
- token-classification
---
# Mountain Names NER Dataset
## Dataset Description
A Named Entity Recognition dataset focused on identifying mountain names in text.
The dataset contains tokenized text with corresponding NER tags where:
- Tag 1: Mountain name
- Tag 0: Not a mountain name
## Dataset Structure
The dataset contains two main columns:
- `tokens`: List of tokenized words
- `tags`: Corresponding NER tags (0 or 1)
## Example:
```python
{
'tokens': ['The', 'Everest', 'is', 'the', 'highest', 'peak'],
'tags': [0, 1, 0, 0, 0, 0]
}
```
## Usage:
```python
from datasets import load_dataset
dataset = load_dataset("Gepe55o/mountain-ner-dataset")
train_data = dataset["train"]
test_data = dataset["test"]
```
## Dataset creation:
- Source data collected from [NERetrive](https://arxiv.org/pdf/2310.14282) and [Few-NERD](https://arxiv.org/pdf/2105.07464v6) datasets
- Filtered for mountain-related entities
- Converted to binary classification (mountain/non-mountain)
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