{"url":"/dataset/glucose","name":"GLUCOSE","full_name":null,"description_markdown":"**GLUCOSE** is a large-scale dataset of implicit commonsense causal knowledge, encoded as causal mini-theories about the world, each grounded in a narrative context. To construct GLUCOSE, we drew on cognitive psychology to identify ten dimensions of causal explanation, focusing on events, states, motivations, and emotions. Each GLUCOSE entry includes a story-specific causal statement paired with an inference rule generalized from the statement.\r\n\r\nSource: [GLUCOSE: GeneraLized and COntextualized Story Explanations](https://paperswithcode.com/paper/glucose-generalized-and-contextualized-story)\r\n\r\nImage source: [GLUCOSE: GeneraLized and COntextualized Story Explanations](https://arxiv.org/pdf/2009.07758v2.pdf)","description_withheld":null,"homepage":"https://github.com/ElementalCognition/glucose/","introduced_date":"2020-09-16","introduced_date_note":null,"introduced_by":{"paper":"/paper/glucose-generalized-and-contextualized-story","title":"GLUCOSE: GeneraLized and COntextualized Story Explanations","first_author":"Nasrin Mostafazadeh","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["GLUCOSE"],"data_loaders":[{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/community-datasets/glucose","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/glucose","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/ElementalCognition/glucose","url":"https://github.com/ElementalCognition/glucose","frameworks":[]}],"num_papers_in_archive":33,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}