Knowledge-Based Ontology Editor Natural Language Interface
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Solution Overview
Problem
Current ontology editors lack efficient methods for semantically parsing and updating knowledge bases using natural language inputs, leading to suboptimal editing and confidence scoring in ontology editing processes.
Innovation Solution
A system and method for natural language and knowledge-based editing that involves receiving a language instance, semantically parsing it to detect ontologies, mapping nodes based on an ontology database and knowledge base, determining node definitions, and assigning a confidence score to update the knowledge base when the score meets a predefined threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If semantic parsing is implemented to detect ontologies from natural language inputs, then the accuracy of ontology detection is improved, but the system complexity increases
Solution Approach 1:
The patent introduces an intermediary confidence scoring mechanism that bridges natural language input and ontology detection. The system parses language instances, maps them to ontology nodes, and assigns confidence scores to each mapping. This intermediary layer allows the system to handle complexity by breaking down the detection process into manageable steps with quantifiable confidence levels, resolving the contradiction between improved detection accuracy and system complexity.
2Reliability
If confidence scoring is applied to filter ontology updates, then data integrity is improved, but the processing time increases
Solution Approach 1:
The patent changes the parameter of ontology node acceptance from binary (accept/reject) to continuous (confidence score). By assigning confidence scores ranging from 0 to 1 to each ontology node mapping, the system can filter updates based on threshold values. This parameter change allows for efficient processing by enabling batch operations on nodes with sufficient confidence while maintaining data integrity through the threshold mechanism, thus resolving the contradiction between reliability and processing time.
3Ease of operation
If natural language processing is used for ontology editing, then ease of operation is improved, but the precision of ontology definition decreases
Solution Approach 1:
The patent implements feedback through confidence score reporting to the user. When a user inputs natural language for ontology editing, the system processes the input, maps it to ontology nodes, and provides confidence scores indicating the reliability of each mapping. This feedback loop allows users to review and adjust mappings with low confidence, thereby maintaining ease of natural language operation while ensuring precision in the final ontology definition through informed user decisions.
Data Source
AI summary
A computer-implemented method for knowledge based ontology editing, is provided. The method receives a language instance to update a knowledge base, using a computer. The method semantically parses the language instance to detect an ontology for editing. The method maps one or more nodes for the ontology for editing based on an ontology database and the knowledge base. The method determines whether the mapped nodes are defined or undefined within the knowledge base. The method calculates a first confidence score based on a number of the defined and undefined mapped nodes. Furthermore, the method updates the knowledge base when the first confidence score meets a pre-defined threshold.