Conversational Interface for Relational Database Querying
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Solution Overview
Problem
Relational databases are difficult to query for non-technical users due to the need for knowledge of structured query language (SQL) and specific database models, limiting accessibility and requiring technical expertise for data analysis.
Innovation Solution
A method and system that convert natural language queries into controlled natural language, which is then translated into SQL queries, allowing users to interact with relational databases using conversational analytics, enabling a wider range of users to access and analyze data without SQL knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If natural language commands are used to query databases, then ease of operation is improved, but reliability deteriorates due to lack of exact correspondence between natural language and database queries
Solution Approach 1:
The patent introduces controlled natural language as an intermediary layer between natural language commands and structured query language. The system first converts natural language to controlled natural language (which has a one-to-one correspondence with SQL), then translates controlled natural language to SQL queries. This two-stage translation process maintains reliability while improving ease of operation, as controlled natural language serves as a precise intermediate representation that eliminates the ambiguity of direct natural language-to-SQL translation.
2Reliability
If controlled natural language is introduced as an intermediary, then reliability is improved through one-to-one correspondence with SQL, but device complexity increases
Solution Approach 1:
The patent segments the query translation process into two distinct stages: first converting natural language to controlled natural language, then converting controlled natural language to SQL. This segmentation allows each translation stage to be optimized independently, with controlled natural language providing a structured intermediate representation that simplifies the overall translation complexity while maintaining high reliability through its one-to-one correspondence with SQL syntax.
Data Source
AI summary
A conversational analytics system may provide for a conversational interface to any relational database. A controlled natural language may be constructed in an automated manner from a given database (e.g., from schema and values associated with a relational database). For instance, a user natural language expression may be converted to an expression in the constructed controlled natural language and the controlled natural language expression may be converted into a sequence of one or more queries in a query language (e.g., queries in structured query language (SQL)). Such an intermediate controlled natural language may provide queries without ambiguity (e.g., as each expression or phrase in the controlled natural language may be mapped to one sequence of SQL queries). Accordingly, any natural language user utterance that ultimately follows the controlled natural language may be automatically converted into a sequence of one or more SQL queries sent to the database.