{"url":"/dataset/tickettalk","name":"TicketTalk","full_name":null,"description_markdown":"A movie ticketing dialog dataset with 23,789 annotated conversations. The movie ticketing conversations range from completely open-ended and unrestricted to more structured, both in terms of their knowledge base, discourse features, and number of turns. In qualitative human evaluations, model-generated responses trained on just 10,000 TicketTalk dialogs were rated to \"make sense\" 86.5 percent of the time, almost the same as human responses in the same contexts.\r\n\r\nSource: [TicketTalk: Toward human-level performance with end-to-end, transaction-based dialog systems](/paper/tickettalk-toward-human-level-performance)","description_withheld":null,"homepage":"https://github.com/google-research-datasets/Taskmaster/tree/master/TM-3-2020","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/tickettalk-toward-human-level-performance","title":"TicketTalk: Toward human-level performance with end-to-end, transaction-based dialog systems","first_author":"Bill Byrne","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[],"languages":[],"variants":["TicketTalk"],"data_loaders":[{"repo":"https://github.com/google-research-datasets/Taskmaster","url":"https://github.com/google-research-datasets/Taskmaster","frameworks":[]}],"num_papers_in_archive":2,"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."}