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Text-To-SQL

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하위 태스크: 1
평가표: 10
보존된 평가 기록: 86

Text-to-SQL is a task in natural language processing (NLP) where the goal is to automatically generate SQL queries from natural language text. The task involves converting the text input into a structured representation and then using this representation to generate a semantically correct SQL query that can be executed on a database.

<span style="color:grey; opacity: 0.6">( Image credit: SyntaxSQLNet )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/bgunlp/qpl

공식 코드

Semantic Decomposition of Question and SQL for Text-to-SQL Parsing

https://github.com/bigbigwatermalon/c3sql

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C3: Zero-shot Text-to-SQL with ChatGPT

https://github.com/brunnurs/valuenet

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ValueNet: A Natural Language-to-SQL System that Learns from Database Information

https://github.com/c4ai/gap-text2sql

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mRAT-SQL+GAP:A Portuguese Text-to-SQL Transformer

https://github.com/c4ai/integrating-question-answering-and-text-to-sql-in-portuguese

공식 코드

Integrating question answering and text-to-SQL in Portuguese

https://github.com/cen-jipeng-suda/sqlfixagent

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SQLFixAgent: Towards Semantic-Accurate Text-to-SQL Parsing via Consistency-Enhanced Multi-Agent Collaboration

https://github.com/chatc/TriageSQL

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Did You Ask a Good Question? A Cross-Domain Question Intention Classification Benchmark for Text-to-SQL

https://github.com/chiahsuan156/KaggleDBQA

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KaggleDBQA: Realistic Evaluation of Text-to-SQL Parsers

https://github.com/cuplv/text-to-sql-wizardcoder

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Analyzing the Effectiveness of Large Language Models on Text-to-SQL Synthesis

https://github.com/cycloneboy/base_sql

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BASE-SQL: A powerful open source Text-To-SQL baseline approach

https://github.com/cycloneboy/csc_sql

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CSC-SQL: Corrective Self-Consistency in Text-to-SQL via Reinforcement Learning

https://github.com/czbnlp/LPE-SQL

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Leveraging Prior Experience: An Expandable Auxiliary Knowledge Base for Text-to-SQL

https://github.com/dakingrai/ood-generalization-semantic-boundary-techniques

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Improving Generalization in Language Model-Based Text-to-SQL Semantic Parsing: Two Simple Semantic Boundary-Based Techniques

https://github.com/dmirlab-group/sadga

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SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL

https://github.com/eosphoros-ai/db-gpt

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Demonstration of DB-GPT: Next Generation Data Interaction System Empowered by Large Language Models

https://github.com/exploration-lab/booksql

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

https://github.com/facebookresearch/tabert

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TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data

https://github.com/facebookresearch/video-nonlocal-net

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Non-local Neural Networks

https://github.com/felix01189/seed

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SEED: Enhancing Text-to-SQL Performance and Practical Usability Through Automatic Evidence Generation

https://github.com/flyingfeather/dea-sql

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Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm

https://github.com/glee4810/EHRSQL

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EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Records

https://github.com/google-research/language

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Unlocking Compositional Generalization in Pre-trained Models Using Intermediate Representations

https://github.com/guotong1988/NL2SQL-BERT

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Content Enhanced BERT-based Text-to-SQL Generation

https://github.com/guotong1988/NL2SQL-RULE

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Content Enhanced BERT-based Text-to-SQL Generation

https://github.com/guotong1988/Rule-SQL

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Using Database Rule for Weak Supervised Text-to-SQL Generation

https://github.com/headacheboy/IGSQL

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IGSQL: Database Schema Interaction Graph Based Neural Model for Context-Dependent Text-to-SQL Generation

https://github.com/heegyukim/flex

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FLEX: Expert-level False-Less EXecution Metric for Reliable Text-to-SQL Benchmark

https://github.com/hirupert/sede

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Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data

https://github.com/hkustdial/nl2sql_handbook

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A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?

https://github.com/hongwin/schema-r1

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Schema-R1: A reasoning training approach for schema linking in Text-to-SQL Task

https://github.com/huybery/r2sql

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Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing

https://github.com/hyan5/learning_to_simulate_nl_feedback

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Learning to Simulate Natural Language Feedback for Interactive Semantic Parsing

https://github.com/imayk/crush4sql

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CRUSH4SQL: Collective Retrieval Using Schema Hallucination For Text2SQL

https://github.com/jayetri/DrugEHRQA-A-Question-Answering-Dataset-on-Structured-and-Unstructured-Electronic-Health-Records

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DrugEHRQA: A Question Answering Dataset on Structured and Unstructured Electronic Health Records For Medicine Related Queries

https://github.com/jf87/footballdb

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Evaluating the Data Model Robustness of Text-to-SQL Systems Based on Real User Queries

https://github.com/jkkummerfeld/text2sql-data

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Improving Text-to-SQL Evaluation Methodology

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