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Text-To-Sql

12 papers with code · Computer Code

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SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning

ICLR 2018 salesforce/WikiSQL

Existing state-of-the-art approaches rely on reinforcement learning to reward the decoder when it generates any of the equivalent serializations.

TEXT-TO-SQL

Improving Text-to-SQL Evaluation Methodology

ACL 2018 jkkummerfeld/text2sql-data

Second, we show that the current division of data into training and test sets measures robustness to variations in the way questions are asked, but only partially tests how well systems generalize to new queries; therefore, we propose a complementary dataset split for evaluation of future work.

TEXT-TO-SQL

Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task

EMNLP 2018 taoyds/spider

We define a new complex and cross-domain semantic parsing and text-to-SQL task where different complex SQL queries and databases appear in train and test sets.

SEMANTIC PARSING TEXT-TO-SQL

SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-DomainText-to-SQL Task

11 Oct 2018taoyds/syntaxsql

In this paper we propose SyntaxSQLNet, a syntax tree network to address the complex and cross-domain text-to-SQL generation task.

SEMANTIC PARSING TEXT-TO-SQL

TypeSQL: Knowledge-based Type-Aware Neural Text-to-SQL Generation

NAACL 2018 taoyds/typesql

Interacting with relational databases through natural language helps users of any background easily query and analyze a vast amount of data.

SLOT FILLING TEXT-TO-SQL

Robust Text-to-SQL Generation with Execution-Guided Decoding

9 Jul 2018Microsoft/PointerSQL

We consider the problem of neural semantic parsing, which translates natural language questions into executable SQL queries.

SEMANTIC PARSING TEXT-TO-SQL

CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases

11 Sep 2019ryanzhumich/sparc_atis_pytorch

We present CoSQL, a corpus for building cross-domain, general-purpose database (DB) querying dialogue systems.

DIALOGUE STATE TRACKING TEXT-TO-SQL

Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions

2 Sep 2019ryanzhumich/sparc_atis_pytorch

We focus on the cross-domain context-dependent text-to-SQL generation task.

TEXT-TO-SQL

SParC: Cross-Domain Semantic Parsing in Context

ACL 2019 ryanzhumich/sparc_atis_pytorch

The best model obtains an exact match accuracy of 20. 2% over all questions and less than10% over all interaction sequences, indicating that the cross-domain setting and the con-textual phenomena of the dataset present significant challenges for future research.

SEMANTIC PARSING TEXT-TO-SQL