{"url":"/dataset/aaac","name":"AAAC","full_name":"Artificial Argument Analysis Corpus","description_markdown":"DeepA2 is a modular framework for deep argument analysis. DeepA2 datasets contain comprehensive logical reconstructions of informally presented arguments in short argumentative texts. This item references two two synthetic DeepA2 datasets for artificial argument analysis: AAAC01 and AAAC02.","description_withheld":null,"homepage":"https://huggingface.co/datasets/debatelab/aaac","introduced_date":"2021-10-04","introduced_date_note":null,"introduced_by":{"paper":"/paper/deepa2-a-modular-framework-for-deep-argument","title":"DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language Models","first_author":"Gregor Betz","url":null},"license":{"name":"cc-by-sa-4.0","url":null},"modalities":[],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["AAAC"],"data_loaders":[{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/DebateLabKIT/aaac","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/debatelab/aaac","frameworks":["tf","pytorch","jax"]}],"num_papers_in_archive":1,"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":"2026-09-25T09:33:49+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."}