We present 20min-XD (20 Minuten cross-lingual document-level), a French-German, document-level comparable corpus of news articles, sourced from the Swiss online news outlet 20 Minuten/20 minutes. Our dataset comprises around 15,000 article pairs spanning 2015 to 2024, automatically aligned based on semantic similarity. We detail the data collection process and alignment methodology. Furthermore, we provide a qualitative and quantitative analysis of the corpus. The resulting dataset exhibits a broad spectrum of cross-lingual similarity, ranging from near-translations to loosely related articles, making it valuable for various NLP applications and broad linguistically motivated studies. We publicly release the dataset in document- and sentence-aligned versions and code for the described experiments.
@article{arxiv.2504.21677,
title = {20min-XD: A Comparable Corpus of Swiss News Articles},
author = {Michelle Wastl and Jannis Vamvas and Selena Calleri and Rico Sennrich},
journal= {arXiv preprint arXiv:2504.21677},
year = {2025}
}