{"url":"/dataset/eracond","name":"ErAConD","full_name":"Error Annotated Conversational Dialog Dataset for Grammatical Error Correction","description_markdown":"ErAConD is a novel GEC dataset consisting of parallel original and corrected utterances drawn from open-domain chatbot conversations.\r\n\r\nWe collected 186 dialogs containing 1735 user utterance turns of open-domain dialog data by deploying BlenderBot on Amazon Mechanical Turk (AMT) via LEGOEval.\r\n\r\nThis dataset is, to our knowledge, the first GEC dataset targeted to a human-machine conversational setting.","description_withheld":null,"homepage":"https://github.com/yuanxun-yx/eracond","introduced_date":"2021-12-15","introduced_date_note":null,"introduced_by":{"paper":"/paper/eracond-error-annotated-conversational-dialog","title":"ErAConD : Error Annotated Conversational Dialog Dataset for Grammatical Error Correction","first_author":"Xun Yuan","url":null},"license":{"name":"MIT License","url":null},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["ErAConD"],"data_loaders":[],"num_papers_in_archive":3,"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."}