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Text-To-Sql

13 papers with code · Computer Code

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RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers

ICLR 2020

In addition, we observe qualitative improvements in the model’s understanding of schema linking and alignment.

SEMANTIC PARSING TEXT-TO-SQL

Content Enhanced BERT-based Text-to-SQL Generation

16 Oct 2019

We present a simple methods to leverage the table content for the BERT-based model to solve the text-to-SQL problem.

TEXT-TO-SQL

Model-based Interactive Semantic Parsing: A Unified Framework and A Text-to-SQL Case Study

11 Oct 2019

As a promising paradigm, interactive semantic parsing has shown to improve both semantic parsing accuracy and user confidence in the results.

SEMANTIC PARSING TEXT-TO-SQL

Global Reasoning over Database Structures for Text-to-SQL Parsing

29 Aug 2019

State-of-the-art semantic parsers rely on auto-regressive decoding, emitting one symbol at a time.

GRAPH NEURAL NETWORK SEMANTIC PARSING TEXT-TO-SQL

Zero-shot Text-to-SQL Learning with Auxiliary Task

29 Aug 2019

Recent years have seen great success in the use of neural seq2seq models on the text-to-SQL task.

TEXT-TO-SQL

SParC: Cross-Domain Semantic Parsing in Context

ACL 2019

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

Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation

ACL 2019

We present a neural approach called IRNet for complex and cross-domain Text-to-SQL.

TEXT-TO-SQL

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

ACL 2019

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.

GRAPH NEURAL NETWORK TEXT-TO-SQL

Grammar-based Neural Text-to-SQL Generation

30 May 2019

The sequence-to-sequence paradigm employed by neural text-to-SQL models typically performs token-level decoding and does not consider generating SQL hierarchically from a grammar.

SEMANTIC PARSING TEXT-TO-SQL

Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation

ACL 2019

We present a neural approach called IRNet for complex and cross-domain Text-to-SQL.

TEXT-TO-SQL