metadata
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
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:
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