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Datasets

Greatest papers with code

SeqGenSQL -- A Robust Sequence Generation Model for Structured Query Language

7 Nov 2020salesforce/WikiSQL

We explore using T5 (Raffel et al. (2019)) to directly translate natural language questions into SQL statements.

TEXT GENERATION TEXT-TO-SQL

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

TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data

ACL 2020 facebookresearch/tabert

Recent years have witnessed the burgeoning of pretrained language models (LMs) for text-based natural language (NL) understanding tasks.

SEMANTIC PARSING TEXT-TO-SQL

Semantic Evaluation for Text-to-SQL with Distilled Test Suites

EMNLP 2020 taoyds/spider

We propose test suite accuracy to approximate semantic accuracy for Text-to-SQL models.

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

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.

SQL PARSING TEXT-TO-SQL

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

ACL 2020 Microsoft/rat-sql

The generalization challenge lies in (a) encoding the database relations in an accessible way for the semantic parser, and (b) modeling alignment between database columns and their mentions in a given query.

SEMANTIC PARSING TEXT-TO-SQL

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

ACL 2019 microsoft/IRNet

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

TEXT-TO-SQL