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20min-XD: A Comparable Corpus of Swiss News Articles

Published: April 30, 2025 | arXiv ID: 2504.21677v1

By: Michelle Wastl , Jannis Vamvas , Selena Calleri and more

Potential Business Impact:

Helps computers understand news in different languages.

Business Areas:
Text Analytics Data and Analytics, Software

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.

Country of Origin
🇨🇭 Switzerland


Page Count
10 pages

Category
Computer Science:
Computation and Language