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This paper presents a 17k-sentence corpus with annotations for argumentative passages across three German political arenas during COVID-19, and a pilot study on automatically identifying such passages, finding that boundaries are hard to pin down and models exhibit confirmation bias.
This paper introduces a linked multimodal dataset of official speeches from the Russian government, including text, images, metadata, and topic annotations, designed to support social science research and LLM applications in political domains.