File size: 1,425 Bytes
400c890
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c11aecc
 
400c890
c11aecc
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
---
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)