Query Token Entity Identification Interface
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Solution Overview
Problem
Users face inefficiencies in formulating and understanding queries for enterprise data due to the complexity of underlying data storage schemas, requiring familiarity with logical objects and query syntax, which overwhelms them as query complexity increases.
Innovation Solution
A user interface system that identifies and visually indicates query tokens with associated entity types, providing query suggestions and corrections, and utilizing fuzzy matching and user profiling to facilitate query formulation and semantic understanding, including graphical feedback and inline suggestions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users formulate queries using conventional query syntax and logical objects, then query functionality is achieved, but user complexity and difficulty increase
Solution Approach 1:
The patent introduces an intermediary system that translates natural language queries into formal query syntax. The system includes a natural language parser, semantic analyzer, and query generator that act as mediators between the user's intuitive language and the complex query language, eliminating the need for users to directly learn and use complex query syntax while still achieving the desired query functionality
Solution Approach 2:
The patent replaces the mechanical system of learning and applying complex query syntax with an automated natural language processing system. Instead of requiring users to manually construct queries using formal syntax rules, the system uses AI-based natural language understanding to automatically generate the appropriate query syntax from casual user input, substituting the manual mechanical process with an intelligent automated one
2Adaptability or versatility
If query functionality is enhanced to handle complex data requirements, then query capability improves, but time and resources expended increase
Solution Approach 1:
The patent implements preliminary action by pre-processing and understanding the user's natural language intent before generating the query. The system performs semantic analysis, entity recognition, and query planning in advance, so when the query is generated, it is already optimized and ready for execution, reducing the overall time required for complex query formulation
Solution Approach 2:
The system provides self-service by automatically understanding user intent, generating appropriate queries, and even suggesting relevant data visualizations without requiring users to manually specify every detail. The query system serves itself by using AI to interpret and translate user needs into executable queries, eliminating the need for users to invest significant time in learning query syntax or constructing complex queries manually
3Measurement precision
If users attempt to understand formulated query semantics, then query accuracy may improve, but user cognitive load increases
Solution Approach 1:
The patent uses an intermediary explanation system that translates the generated query back into natural language explanations for the user. This intermediary layer provides semantic explanations of what the query does, why certain data is selected, and how the query logic works, allowing users to understand query semantics without needing to comprehend the complex formal syntax themselves
Solution Approach 2:
The patent replaces the cognitive mechanism of understanding complex query syntax with an automated explanation generation system. Instead of requiring users to mentally parse and understand formal query language semantics, the system uses natural language generation to explain the query meaning in intuitive terms, substituting the cognitive burden with an automated interpretation service
Data Source
AI summary
A system includes reception of a token input by a user into a user interface, determination, in response to reception of the token, of a query entity associated with the token, the query entity associated with an entity type, and display of a graphical indicator on the user interface in association with the token, the graphical indicator indicating the determined entity type.