Natural Language Database Interface via Dependency Parse Pruning
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Solution Overview
Problem
Current database management systems require users to formulate complex Structured Query Language (SQL) queries, which can be cumbersome, especially for non-technical users, and do not efficiently handle natural language queries, limiting user interaction with databases.
Innovation Solution
A system and method that utilizes natural language processing (NLP) to automatically convert natural language queries into SQL queries by generating multiple dependency parses, identifying entities and relations, and using template rules and schema annotation files to create domain-independent rules for entity detection, enabling users to interact with databases using simple language.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If SQL query language is used for database access, then data retrieval capability is improved, but user operation complexity increases
Solution Approach 1:
The patent introduces a natural language processing system as an intermediary between the user and the SQL query language. The system translates user-friendly natural language queries into SQL commands, allowing users to interact with databases without learning SQL syntax. This mediator handles the complexity of query formulation while presenting a simple interface to users.
Solution Approach 2:
The patent replaces the mechanical process of manually constructing SQL queries with an automated natural language processing system. Instead of requiring users to mechanically assemble SQL syntax according to strict grammatical rules, the system automatically generates appropriate SQL commands from natural language input, substituting the manual mechanical process with an intelligent automated system.
2Ease of operation
If natural language processing is implemented, then ease of use is improved, but system complexity increases
Solution Approach 1:
The patent divides the natural language processing system into distinct functional modules: a parser component that analyzes sentence structure, an entity recognition component that identifies key information, and a query generation component that constructs SQL commands. This segmentation allows each module to handle specific aspects of the translation process, making the overall complex system more manageable and maintainable while providing simple user interaction.
3Reliability
If multiple dependency parses are generated, then query accuracy is improved, but processing time increases
Solution Approach 1:
The patent generates multiple dependency parses of the natural language query to ensure accurate interpretation, but applies pruning rules to eliminate redundant or incorrect parses before final SQL generation. This partial action approach maintains high query accuracy by considering multiple interpretations while reducing processing time by discarding unnecessary parses early in the process rather than processing all possible parses to completion.
Data Source
AI summary
An embodiment of the invention provides a method for including receiving a natural language query from a user with an interface, and generating multiple dependency parses of the natural language query with a parser device connected to the interface. The generating of the multiple dependency parses includes dividing the natural language query into multiple components, and creating a single dependency parse by connecting each component of the components with at least one other component of the components. A processor connected to the parser device applies rules to all of the multiple dependency parses to identify entities and relations in the natural language query.