---
dataset_info:
  features:
  - name: concept_set
    dtype: string
  - name: '1'
    dtype: string
  - name: '2'
    dtype: string
  - name: '3'
    dtype: string
  - name: '4'
    dtype: string
  - name: gold
    dtype: int64
  splits:
  - name: china
    num_bytes: 25567
    num_examples: 99
  - name: english
    num_bytes: 33124
    num_examples: 99
  - name: espanol
    num_bytes: 35535
    num_examples: 99
  - name: japan
    num_bytes: 33329
    num_examples: 99
  - name: korean
    num_bytes: 33419
    num_examples: 99
  download_size: 131071
  dataset_size: 160974
configs:
- config_name: default
  data_files:
  - split: china
    path: data/china-*
  - split: english
    path: data/english-*
  - split: espanol
    path: data/espanol-*
  - split: japan
    path: data/japan-*
  - split: korean
    path: data/korean-*
---


### 🇰🇷🇺🇸🇯🇵🇨🇳🇪🇸 KoCommonGEN v2 Code-switching

This KoCommonGEN v2 Code-switching dataset consists of 99 samples for numerical commonsense reasoning, which were created relying on machine translation.

The dataset can be found on Hugging Face at: [nlpai-lab/ko_commongen_v2_code_switching](https://huggingface.co/datasets/nlpai-lab/ko_commongen_v2_code_switching)

This dataset contains code-switching data for the following languages:
- Korean (korean)
- English (english)
- Japanese (japan)
- Chinese (china)
- Spanish (espanol)

(The code-switching data relies on machine translation, which may result in some inaccuracies.)


To load the dataset, you can use the following code:

```python
from datasets import load_dataset

dataset = load_dataset("nlpai-lab/ko_commongen_v2_code_switching")

# To access a specific language dataset:
korean_data = dataset['korean']
english_data = dataset['english']
# ... and so on for other languages
```