---
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.