mlsanityData to 7 Oct 2026

BookSQL: A Large Scale Text-to-SQL Dataset for Accounting Domain

arXiv 2406.07860 ↗First posted 12 Jun 2024cs.CL cs.AI cs.LGcited by 10

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Abstract (arXiv)

Several large-scale datasets (e.g., WikiSQL, Spider) for developing natural language interfaces to databases have recently been proposed. These datasets cover a wide breadth of domains but fall short on some essential domains, such as finance and accounting. Given that accounting databases are used worldwide, particularly by non-technical people, there is an imminent need to develop models that could help extract information from accounting databases via natural language queries. In this resource paper, we aim to fill this gap by proposing a new large-scale Text-to-SQL dataset for the accounting and financial domain: BookSQL. The dataset consists of 100k natural language queries-SQL pairs, and accounting databases of 1 million records. We experiment with and analyze existing state-of-the-art models (including GPT-4) for the Text-to-SQL task on BookSQL. We find significant performance gaps, thus pointing towards developing more focused models for this domain.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 14 of its 21 references that are in the map. First posted on arXiv 12 Jun 2024.

Builds on

14 of 21 references.

References · 14

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  3. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,120
  4. 2017Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learningcited by 679
  5. 2023Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLscited by 667
  6. 2023DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correctioncited by 465
  7. 2023RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQLcited by 191
  8. 2018Improving Text-to-SQL Evaluation Methodologycited by 133
  9. 2021KaggleDBQA: Realistic Evaluation of Text-to-SQL Parserscited by 105
  10. 2019Text-to-SQL Generation for Question Answering on Electronic Medical Recordscited by 76
  11. 2020Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Trainingcited by 65
  12. 2020On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queriescited by 59
2 more
  1. 2022Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expectcited by 47
  2. 2021Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Datacited by 43

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 6; 2026: 2.

10 papers.

  1. 2024A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?cited by 54
  2. 2024MathBridge: A Large Corpus Dataset for Translating Spoken Mathematical Expressions into LaTeX Formulas for Improved Readabilitycited by 4
  3. 2025Exploring the Landscape of Text-to-SQL with Large Language Models: Progresses, Challenges and Opportunitiescited by 4
  4. 2025RubikSQL: Lifelong Learning Agentic Knowledge Base as an Industrial NL2SQL Systemcited by 4
  5. 2025Structuring the Unstructured: A Multi-Agent System for Extracting and Querying Financial KPIs and Guidancecited by 2
  6. 2025FinStat2SQL: A Text2SQL Pipeline for Financial Statement Analysiscited by 1
  7. 2025Beyond SELECT: A Comprehensive Taxonomy-Guided Benchmark for Real-World Text-to-SQL Translationcited by 1
  8. 2026PExA: Parallel Exploration Agent for Complex Text-to-SQLcited by 1
  9. 2025FINCH: Financial Intelligence using Natural language for Contextualized SQL Handlingcited by 0
  10. 2026RingSQL: Schema-Independent Synthetic Data Generation for Text-to-SQL Reinforcement Learningcited by 0