DongHyun Choi


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RYANSQL: Recursively Applying Sketch-based Slot Fillings for Complex Text-to-SQL in Cross-Domain Databases
DongHyun Choi | Myeong Cheol Shin | EungGyun Kim | Dong Ryeol Shin
Computational Linguistics, Volume 47, Issue 2 - June 2021

Abstract Text-to-SQL is the problem of converting a user question into an SQL query, when the question and database are given. In this article, we present a neural network approach called RYANSQL (Recursively Yielding Annotation Network for SQL) to solve complex Text-to-SQL tasks for cross-domain databases. Statement Position Code (SPC) is defined to transform a nested SQL query into a set of non-nested SELECT statements; a sketch-based slot-filling approach is proposed to synthesize each SELECT statement for its corresponding SPC. Additionally, two input manipulation methods are presented to improve generation performance further. RYANSQL achieved competitive result of 58.2% accuracy on the challenging Spider benchmark. At the time of submission (April 2020), RYANSQL v2, a variant of original RYANSQL, is positioned at 3rd place among all systems and 1st place among the systems not using database content with 60.6% exact matching accuracy. The source code is available at

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OutFlip: Generating Examples for Unknown Intent Detection with Natural Language Attack
DongHyun Choi | Myeong Cheol Shin | EungGyun Kim | Dong Ryeol Shin
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021


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Korean Treebank Transformation for Parser Training
DongHyun Choi | Jungyeul Park | Key-Sun Choi
Proceedings of the ACL 2012 Joint Workshop on Statistical Parsing and Semantic Processing of Morphologically Rich Languages


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Intrinsic Property-based Taxonomic Relation Extraction from Category Structure
DongHyun Choi | Eun-Kyung Kim | Sang-Ah Shim | Key-Sun Choi
Proceedings of the 6th Workshop on Ontologies and Lexical Resources