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Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing

arXiv 1905.06241 ↗First posted 15 May 2019cs.CLcited by 74

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Abstract (arXiv)

Research on parsing language to SQL has largely ignored the structure of the database (DB) schema, either because the DB was very simple, or because it was observed at both training and test time. In Spider, a recently-released text-to-SQL dataset, new and complex DBs are given at test time, and so the structure of the DB schema can inform the predicted SQL query. In this paper, we present an encoder-decoder semantic parser, where the structure of the DB schema is encoded with a graph neural network, and this representation is later used at both encoding and decoding time. Evaluation shows that encoding the schema structure improves our parser accuracy from 33.8% to 39.4%, dramatically above the current state of the art, which is at 19.7%.

Key facts. Cited by 74 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 May 2019.

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Citing papers per year: 2021: 16; 2022: 15; 2023: 13; 2024: 15; 2025: 10; 2026: 5.

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  1. 2023Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLscited by 667
  2. 2021LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relationscited by 119
  3. 2021Towards Robustness of Text-to-SQL Models against Synonym Substitutioncited by 110
  4. 2023Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL Parsingcited by 93
  5. 2021Exploring Underexplored Limitations of Cross-Domain Text-to-SQL Generalizationcited by 92
  6. 2022RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQLcited by 85
  7. 2024A Survey on Employing Large Language Models for Text-to-SQL Taskscited by 67
  8. 2021Natural SQL: Making SQL Easier to Infer from Natural Language Specificationscited by 66
  9. 2023ACT-SQL: In-Context Learning for Text-to-SQL with Automatically-Generated Chain-of-Thoughtcited by 65
  10. 2023How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settingscited by 57
  11. 2024A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?cited by 54
  12. 2024Synthesizing Text-to-SQL Data from Weak and Strong LLMscited by 53
38 more
  1. 2022A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directionscited by 51
  2. 2024RSL-SQL: Robust Schema Linking in Text-to-SQL Generationcited by 51
  3. 2022Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expectcited by 47
  4. 2021SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQLcited by 43
  5. 2021ShadowGNN: Graph Projection Neural Network for Text-to-SQL Parsercited by 35
  6. 2024PURPLE: Making a Large Language Model a Better SQL Writercited by 34
  7. 2022Proton: Probing Schema Linking Information from Pre-trained Language Models for Text-to-SQL Parsingcited by 30
  8. 2023Natural Language Interfaces for Tabular Data Querying and Visualization: A Surveycited by 27
  9. 2022HIE-SQL: History Information Enhanced Network for Context-Dependent Text-to-SQL Semantic Parsingcited by 26
  10. 2022Semantic Enhanced Text-to-SQL Parsing via Iteratively Learning Schema Linking Graphcited by 22
  11. 2022UniSAr: A Unified Structure-Aware Autoregressive Language Model for Text-to-SQLcited by 20
  12. 2022N-Best Hypotheses Reranking for Text-To-SQL Systemscited by 19
  13. 2025Reliable Text-to-SQL with Adaptive Abstentioncited by 19
  14. 2024Metasql: A Generate-then-Rank Framework for Natural Language to SQL Translationcited by 17
  15. 2022Measuring and Improving Compositional Generalization in Text-to-SQL via Component Alignmentcited by 16
  16. 2023Prompting GPT-3.5 for Text-to-SQL with De-semanticization and Skeleton Retrievalcited by 16
  17. 2025STaR-SQL: Self-Taught Reasoner for Text-to-SQLcited by 16
  18. 2021Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsingcited by 15
  19. 2025Think2SQL: Reinforce LLM Reasoning Capabilities for Text2SQLcited by 14
  20. 2023Semantic Decomposition of Question and SQL for Text-to-SQL Parsingcited by 13
  21. 2024ROUTE: Robust Multitask Tuning and Collaboration for Text-to-SQLcited by 13
  22. 2023Retrieval-augmented GPT-3.5-based Text-to-SQL Framework with Sample-aware Prompting and Dynamic Revision Chaincited by 12
  23. 2022Deep Learning Driven Natural Languages Text to SQL Query Conversion: A Surveycited by 11
  24. 2023Towards Understanding the Generalization of Medical Text-to-SQL Models and Datasetscited by 9
  25. 2021SPARQLing Database Queries from Intermediate Question Decompositionscited by 7
  26. 2024Grounding Natural Language to SQL Translation with Data-Based Self-Explanationscited by 7
  27. 2022Speech-to-SQL: Towards Speech-driven SQL Query Generation From Natural Language Questioncited by 6
  28. 2025Graph Neural Networks for Databases: A Surveycited by 6
  29. 2021An Investigation Between Schema Linking and Text-to-SQL Performancecited by 5
  30. 2021Self-supervised Incremental Deep Graph Learning for Ethereum Phishing Scam Detectioncited by 5
  31. 2021Pay More Attention to History: A Context Modelling Strategy for Conversational Text-to-SQLcited by 5
  32. 2022TIE: Topological Information Enhanced Structural Reading Comprehension on Web Pagescited by 4
  33. 2023Wav2SQL: Direct Generalizable Speech-To-SQL Parsingcited by 4
  34. 2021DBTagger: Multi-Task Learning for Keyword Mapping in NLIDBs Using Bi-Directional Recurrent Neural Networkscited by 3
  35. 2021A Globally Normalized Neural Model for Semantic Parsingcited by 2
  36. 2021Prefix-to-SQL: Text-to-SQL Generation from Incomplete User Questionscited by 2
  37. 2024On Linearizing Structured Data in Encoder-Decoder Language Models: Insights from Text-to-SQLcited by 2
  38. 2024Enhancing Text-to-SQL Capabilities of Large Language Models via Domain Database Knowledge Injectioncited by 2

50 most cited of 74 All 74 (JSON)