Mention Extraction and Linking for SQL Query Generation
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Abstract (arXiv)
On the WikiSQL benchmark, state-of-the-art text-to-SQL systems typically take a slot-filling approach by building several dedicated models for each type of slots. Such modularized systems are not only complex butalso of limited capacity for capturing inter-dependencies among SQL clauses. To solve these problems, this paper proposes a novel extraction-linking approach, where a unified extractor recognizes all types of slot mentions appearing in the question sentence before a linker maps the recognized columns to the table schema to generate executable SQL queries. Trained with automatically generated annotations, the proposed method achieves the first place on the WikiSQL benchmark.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Dec 2020.
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Citing papers per year: 2021: 2; 2022: 4; 2023: 1; 2024: 0; 2025: 2.
9 papers.
- 2022A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directionscited by 51
- 2022Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expectcited by 47
- 2021SeaD: End-to-end Text-to-SQL Generation with Schema-aware Denoisingcited by 27
- 2021Improving Text-to-SQL with Schema Dependency Learningcited by 25
- 2025Reliable Text-to-SQL with Adaptive Abstentioncited by 19
- 2022Uni-Parser: Unified Semantic Parser for Question Answering on Knowledge Base and Databasecited by 16
- 2025MaskSQL: Safeguarding Privacy for LLM-Based Text-to-SQL via Abstractioncited by 3
- 2022Improving Text-to-SQL Semantic Parsing with Fine-grained Query Understandingcited by 0
- 2023Translating Natural Language Queries to SQL Using the T5 Modelcited by 0
- 2025MaskSQL: Safeguarding Privacy for LLM-Based Text-to-SQL via Abstraction27 Sep 2025
- 2025Reliable Text-to-SQL with Adaptive Abstention18 Jan 2025
- 2023Translating Natural Language Queries to SQL Using the T5 Model12 Dec 2023
- 2022Uni-Parser: Unified Semantic Parser for Question Answering on Knowledge Base and Database9 Nov 2022
- 2022Improving Text-to-SQL Semantic Parsing with Fine-grained Query Understanding28 Sep 2022
- 2022A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directions29 Aug 2022
- 2022Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expect22 Aug 2022
- 2021SeaD: End-to-end Text-to-SQL Generation with Schema-aware Denoising17 May 2021
- 2021Improving Text-to-SQL with Schema Dependency Learning7 Mar 2021