Question-answering system using natural language processing with NLIDB approach

With increasing information, lot amount of data is stored in relational databases in organized manner. Structured query language (SQL) is primarily used for extracting information from a relational database and allows us to manage and access process on database. But this is insufficient as not all users are accustomed to write SQL queries if the user question is in Natural language (NL). Hence there is a need to develop a system where non-sophisticated users can access data freely without going into technicality by asking question in Natural language. This paper focuses on creating semantic analyzer for automatic Question-answering system for domain specific database. It provides user with the relevant answers to the user questions using Natural Language processing (NLP) and Natural language interface for database (NLIDB). NLIDB are the systems that translate a natural language sentence into a database query. It contains the stepwise description on conversion of question to simple SQL query without using any clauses. It portrays completely automatic, reliable, fast way to query a database. Hence, Natural language processing techniques applied on English text is converted to SQL query using series of steps like lowercase conversion, tokenization, chunking, generation of SQL query and mapping the query to the database.