{"url":"/dataset/cosql","name":"CoSQL","full_name":"Conversational Text-to-SQL Challenge","description_markdown":"CoSQL is a corpus for building cross-domain, general-purpose database (DB) querying dialogue systems. It consists of 30k+ turns plus 10k+ annotated SQL queries, obtained from a Wizard-of-Oz (WOZ) collection of 3k dialogues querying 200 complex DBs spanning 138 domains. Each dialogue simulates a real-world DB query scenario with a crowd worker as a user exploring the DB and a SQL expert retrieving answers with SQL, clarifying ambiguous questions, or otherwise informing of unanswerable questions. \r\n\r\nSource: [CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases](https://arxiv.org/abs/1909.05378)","description_withheld":null,"homepage":"https://yale-lily.github.io/cosql","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/cosql-a-conversational-text-to-sql-challenge","title":"CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases","first_author":"Tao Yu","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Semantic Parsing","url":"/task/semantic-parsing","datasets_with_task":"/datasets/task/semantic-parsing"},{"name":"Text-To-SQL","url":"/task/text-to-sql","datasets_with_task":"/datasets/task/text-to-sql"},{"name":"Dialogue State Tracking","url":"/task/dialogue-state-tracking","datasets_with_task":"/datasets/task/dialogue-state-tracking"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["CoSQL"],"data_loaders":[],"num_papers_in_archive":45,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/dialogue-state-tracking-on-cosql","task":"Dialogue State Tracking","dataset_variant":"CoSQL","rows":9,"metrics":["question match accuracy","interaction match accuracy"],"first_row_in_archive_order":{"model":"RASAT+PICARD","paper":"/paper/rasat-integrating-relational-structures-into","metrics":{"interaction match accuracy":"26.5","question match accuracy":"55.7"},"code_links":[{"title":"lumia-group/rasat","url":"https://github.com/lumia-group/rasat"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/rasat-integrating-relational-structures-into","title":"RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL","date":"2022-05-14","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":0,"samples_unverified":9,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/hie-sql-history-information-enhanced-network","title":"HIE-SQL: History Information Enhanced Network for Context-Dependent Text-to-SQL Semantic Parsing","date":"2021-11-16","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/picard-parsing-incrementally-for-constrained","title":"PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models","date":"2021-09-10","rows_on_this_dataset":1,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":4,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/dynamic-hybrid-relation-network-for-cross","title":"Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing","date":"2021-01-05","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/score-pre-training-for-context-representation","title":"SCoRe: Pre-Training for Context Representation in Conversational Semantic Parsing","date":"2021-01-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/grounded-adaptation-for-zero-shot-executable","title":"Grounded Adaptation for Zero-shot Executable Semantic Parsing","date":"2020-09-16","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":0,"samples_unverified":11,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/cosql-a-conversational-text-to-sql-challenge","title":"CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases","date":"2019-09-11","rows_on_this_dataset":2,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":1,"samples_unverified":10,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/editing-based-sql-query-generation-for-cross","title":"Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions","date":"2019-09-02","rows_on_this_dataset":1,"code_links":3,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":4,"samples_harvested":38,"samples_ran":5,"samples_unverified":33,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":2,"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."}