{"url":"/dataset/sparc","name":"SParC","full_name":"Semantic Parsing in Context","description_markdown":"**SParC** is a large-scale dataset for complex, cross-domain, and context-dependent (multi-turn) semantic parsing and text-to-SQL task (interactive natural language interfaces for relational databases).\r\n\r\nSource: [https://github.com/taoyds/sparc](https://github.com/taoyds/sparc)\r\nImage Source: [https://arxiv.org/pdf/1906.02285.pdf](https://arxiv.org/pdf/1906.02285.pdf)","description_withheld":null,"homepage":"https://github.com/taoyds/sparc","introduced_date":"2019-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/sparc-cross-domain-semantic-parsing-in","title":"SParC: Cross-Domain Semantic Parsing in Context","first_author":"Tao Yu","url":null},"license":{"name":"Unknown","url":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":"Data Augmentation","url":"/task/data-augmentation","datasets_with_task":"/datasets/task/data-augmentation"}],"languages":[],"variants":["SParC"],"data_loaders":[{"repo":"https://github.com/taoyds/sparc","url":"https://github.com/taoyds/sparc","frameworks":[]}],"num_papers_in_archive":59,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/text-to-sql-on-sparc","task":"Text-To-SQL","dataset_variant":"SParC","rows":7,"metrics":["interaction match accuracy","question match accuracy"],"first_row_in_archive_order":{"model":"RASAT+PICARD","paper":"/paper/rasat-integrating-relational-structures-into","metrics":{"interaction match accuracy":"45.2","question match accuracy":"67.7"},"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"},{"leaderboard":"/sota/semantic-parsing-on-sparc","task":"Semantic Parsing","dataset_variant":"SParC","rows":1,"metrics":["Exact"],"first_row_in_archive_order":{"model":"MeMCE","paper":"/paper/memory-based-semantic-parsing","metrics":{"Exact":"40.3"},"code_links":[{"title":"worksheets/0xbd49d04e","url":"https://worksheets.codalab.org/worksheets/0xbd49d04e5a494a978642bbaf028b659b"}]},"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/pay-more-attention-to-history-a-context","title":"Pay More Attention to History: A Context Modelling Strategy for Conversational Text-to-SQL","date":"2021-12-16","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"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/memory-based-semantic-parsing","title":"Memory-Based Semantic Parsing","date":"2021-09-07","rows_on_this_dataset":1,"code_links":1,"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/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},{"paper":"/paper/syntaxsqlnet-syntax-tree-networks-for-complex","title":"SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-DomainText-to-SQL Task","date":"2018-10-11","rows_on_this_dataset":1,"code_links":2,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":20,"samples_ran":0,"samples_unverified":20,"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."}