SemEval-2022 Task 8: Multilingual news article similarity

This dataset contains pairs of news articles drawn from the first half of 2020 and annotated for seven aspects of similarity: <strong>GEO</strong>: How similar is the geographic focus (places, cities, countries, etc.) of the two articles? <strong>ENT:</strong> How similar are the named entities (e.g., people, companies, organizations, products, named living beings), excluding previously considered locations appearing in the two articles? <strong>TIME</strong> Are the two articles relevant to similar time periods or describing similar time periods? <strong>NAR</strong> How similar are the narrative schemas presented in the two articles? <strong>OVERALL</strong> Overall, are the two articles covering the same substantive news story? (excluding style, framing, and tone) <strong>STYLE</strong> Do the articles have similar writing styles? <strong>TONE</strong> Do the articles have similar tones? Further details are provided in Chen et al. (2022). SemEval-2022 Task 8: Multilingual news article similarity. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022). https://aclanthology.org/2022.semeval-1.155/ The data in this repository includes pairs of URLs and annotations. The text of webpages is generally via the Internet Archive in this special collection: https://archive.org/details/2020-multilingual-news-article-similarity . A script to download and process the webpages is available at https://github.com/euagendas/semeval_8_2022_ia_downloader .