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01ganchengguang /Text-Classification-and-Relation-Event-Extraction-Mix-datasetsThe paper of GIELLM dataset. https://arxiv.org/abs/2311.06838 Cite: @article{gan2023giellm, title={Giellm: Japanese general information extraction large language model utilizing mutual reinforcement effect}, author={Gan, Chengguang and Zhang, Qinghao and Mori, Tatsunori}, journal={arXiv preprint arXiv:2311.06838}, year={2023} } The dataset constructed base in livedoor news corpus 関口宏司 https://www.rondhuit.com/download.html texttext-classification1K<n<10K1 likes37 downloads2y agoHugging Face02extreme-weather-impacts /event_impact_data event_id: ID of the event in the NOAA billion-dollar dataset cik: unique company identifier [If this combination is present, then there was a firm-event impact] asset, economic_flows, none: classification dimensions of the impact channel classifier; shows whether at least one document indicated an asset impact (asset==1), a pure economic flow impact, i.e. at least one document was only addressing an impact through economic flows and NOT through assets as well (economic_flows==1), or none if… See the full description on the dataset page: https://huggingface.co/datasets/extreme-weather-impacts/event_impact_data.tabular10K<n<100K0 likes13 downloads8mo agoHugging Face03hsuvaskakoty /event_timelines_datasettexttext-classification1K<n<10K0 likes9 downloads1y agoHugging Face04adamnik /event_detection_datasettext1K<n<10K1 likes5 downloads4y agoHugging Face05Evilafo /ticket_event_datasettextn<1K0 likes2 downloads1y agoHugging Face06andreaskouv /event_prolog_datatextn<1K0 likes1 downloads2y agoHugging Face

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