Structured Data Graphs for Consistent Natural Language Generation
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Solution Overview
Problem
Current methods for generating technical and legal writings are time-consuming and lack consistency, making it difficult to analyze and reuse the content, with existing automated tools offering limited editorial support.
Innovation Solution
A system and method for generating structured blocks of natural language using a digital data store with a data graph schema, allowing for recursive storage of natural language data units and relation data units that define semantic, thematic, logic, and quantity relations, enabling efficient text generation and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual text editing is used to generate technical and legal writings, then the writing can be created with flexibility, but the process is time-consuming and does not guarantee consistency
Solution Approach 1:
The patent replaces manual mechanical text editing with an automated computerized system that uses data graphs and templates to generate technical and legal writings. This substitution eliminates manual inconsistencies while maintaining flexibility through programmable parameters and reusable templates, simultaneously improving both productivity and reliability.
Solution Approach 2:
The system allows dynamic parameter configuration in data graphs and templates, enabling users to modify writing content by changing parameters rather than manually editing text. This parameter-driven approach ensures consistency through standardized templates while improving productivity through automated parameter substitution and document generation.
2Productivity
If automated proofreading and text processing tools are used, then some editorial tasks are alleviated, but their abilities are very limited for comprehensive editorial purposes
Solution Approach 1:
The patent creates a universal system that combines multiple editorial functions (proofreading, template management, data graph manipulation, automated writing generation) into a single integrated platform. This multi-functional system exceeds the limited capabilities of traditional standalone proofreading tools by providing comprehensive editorial support across the entire document creation process.
Solution Approach 2:
The system segments the writing process into distinct components (data graphs, templates, parameters, relation data units) that can be independently managed and combined. This segmentation allows for specialized processing of different document elements while maintaining overall coordination, enhancing both editorial efficiency and versatility.
3Reliability
If traditional text templates are used for writing, then some consistency can be maintained, but the writing is still difficult to analyze and re-use by computers
Solution Approach 1:
The patent replaces traditional text-based templates with structured data graphs and machine-readable templates that inherently encode semantic relationships and document structure. This substitution makes the writing system natively compatible with computerized analysis while maintaining consistency through standardized data structures and relations.
Solution Approach 2:
The system introduces data graphs as an intermediary layer between human authors and computer processing. These data graphs serve as structured intermediaries that preserve semantic meaning in a machine-readable format, enabling both consistent document generation and easy computerized analysis without losing the nuances of natural language.
4Ease of operation
If manual editorial work is required to change content, then precise control over writing can be achieved, but the process becomes time-consuming
Solution Approach 1:
The system enables content modification through parameter changes in data graphs and templates rather than manual text editing. Users can update document content by modifying parameters, which automatically propagates changes throughout the document structure, dramatically reducing the effort and time required for content updates while maintaining precise control.
Solution Approach 2:
The system performs preliminary structuring of content in data graphs and templates before actual document generation. This preliminary organization allows for efficient bulk updates and automatic propagation of changes, reducing the need for manual editorial work when content needs to be modified.
Data Source
AI summary
The invention relates to a system and method for generating a block of natural language, the system comprising a digital data store capable of storing a data graph according to a data schema, input sub-system for entering natural language data units to the data graph, and a data processor for generating a block of natural language based on the data graph. Further, the data schema allows storage of recursively nested natural language data units and relation data units associated with the natural language data units into the data graph, the relation data units being configured to define relations between natural language data units in the data graph. The data processor is adapted to generate said block of natural language utilizing a plurality of natural language data units and relations between the natural language data units as defined by the relation data units associated therewith.