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21A Comparative Study of Different Techniques of Text-to-SQL Query Converter

Kuldeep Vayadande^1*, Preeti A. Bailke¹, Vikas Janu Nandeshwar¹, R. Kumar² and Varsha R. Dange¹

¹Vishwakarma Institute of Technology, Pune, Maharashtra, India

²VIT-AP University, Inavolu, Beside AP Secretariat, Amaravati, AP, India

Abstract

Converting text to SQL technologies eliminates the requirement for structured languages like SQL by enabling anyone to inspect the RDBMS by submitting questions. Due to the extensive search area, neural semantic parsers (NSPs) frequently fail to convert lengthy and complex utterances into the nested Structured query language (SQL) queries. Natural language query responses over tables are typically viewed as semantic parsing tasks. It is difficult to train semantic parsers from subpar supervision since logical forms produced are only employed as a stage before recovering the connotation. The objective or goal of this comparison in the research is to study all the existing systems for text-to-SQL conversion and then find out the drawback of each system. This paper presents the comparison among the different text-to-SQL conversion systems. Our thorough assessment tries to close a significant knowledge gap regarding the capabilities and limitations of current systems, and it identifies a number of unresolved issues.

Keywords: Tokenization, natural language processing, RDBMS, neural semantic parser, SQL

21.1 Introduction

One of the most crucial facets of semantic parsing ...