The Natural Language Query using NLP by Generation of SQL Query

Abstract

Everyone is having their own personal device that connects to internet. Every user trying to gather the information which they require from internet. Most of the information is assembled in the form of a database. A user who wants to access a database but having limited or lack of knowledge of database languages and find it difficult and challenging situation to access the database. Hence, there is a necessity for a system that enables the users to access the information from the database. Formation of SQL from Natural Language Query using NLP, authors: M Uma, V Sneha and J Bhuvana aims to develop such a system using NLP by giving structured natural language questions as an input and receiving SQL query as an output, to access the related information from the railway reservation database with ease. Five steps are involved in this process, which are tokenization, lemmatization, parts of speech tagging, parsing and mapping. Example: The dataset used for the proposed system has a set of 2880 structured natural language queries on train fare and seats available.