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

We present 20min-XD (20 Minuten crosslingual 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 experiment.

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Publication Details

Journal
Universität Zürich, ZORA
Published
2025-05-15
DOI
https://doi.org/10.5167/uzh-293025
Primary Topic
Computational and Text Analysis Methods
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article
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20min-XD: A Comparable Corpus of Swiss News Articles

Selena Calleri, Michelle Wastl, Rico Sennrich, Jannis Vamvas
Universität Zürich, ZORA
Computational and Text Analysis Methods
article

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

Selena Calleri, Michelle Wastl, Rico Sennrich, Jannis Vamvas
article en

Abstract

We present 20min-XD (20 Minuten crosslingual 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 experiment.

Universität Zürich, ZORA
Quality Education
Openalex Percentile: Top 9%
Computational and Text Analysis Methods
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