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---
dataset_info:
features:
- name: English
dtype: string
- name: Spanish
dtype: string
- name: Italian
dtype: string
splits:
- name: train
num_bytes: 88240.49084249084
num_examples: 218
- name: test
num_bytes: 22262.509157509157
num_examples: 55
download_size: 81258
dataset_size: 110503
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
license: mit
task_categories:
- translation
language:
- en
- es
- it
tags:
- climate
size_categories:
- 1K<n<10K
---
# Dataset Name
<!-- Provide a quick summary of the dataset. -->
Climate Change Multilingual Mini Dataset - ClimateChangeMeasures
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
This is a small parallel dataset consisting of texts related to climate change and environmental topics.
Each entry is aligned in three languages: English, Spanish, and Italian.
### Source Data:
<!-- Provide the basic links for the dataset. -->
- **Repository:** Café Babel was a multilingual weekly magazine focused on European current affairs, culture, and society.
- It was known for publishing content in multiple languages and fostering cross-cultural dialogue among European youth.
- **Current status:** The project is no longer running.
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
While the dataset is too small for training large-scale models from scratch, it can be valuable for:
- Fine-tuning pretrained models for domain adaptation
- Testing multilingual alignment
## Data description:
The articles were human-translated and peer-reviewed to ensure quality and domain accuracy.
## Limitations:
- Small dataset (228 rows) — not suitable for training large-scale models from scratch
- Translations are not strictly literal; they prioritize meaning and naturalness over direct word alignment.
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