Updating Text Output via Document Plan Tree Merging
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Solution Overview
Problem
Natural language generation systems struggle to provide accurate and up-to-date situational awareness, as output text generated at a specific time may become stale by the time it is reviewed, lacking information on changes in complex systems' behavior over time.
Innovation Solution
A method and apparatus that update previously generated output text by analyzing updateable data elements over a defined time window, generating new messages that describe changes, and combining these with original messages to create an updated document plan, which is then processed to produce a revised textual output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If output text is generated at a specific time, then the text provides accurate situational awareness at that moment, but the text becomes stale by the time it is reviewed, lacking information on changes in complex systems' behavior over time
Solution Approach 1:
The system performs preliminary actions by generating the original document plan tree with initial situational awareness text at a specific time. This preliminary output is then updated later with new data elements and changes, allowing the system to prepare accurate information in advance while enabling subsequent updates to maintain timeliness without regenerating the entire text.
Solution Approach 2:
The system implements dynamics by transforming the static original document plan tree into a dynamic updated document plan tree. New data elements are continuously integrated, and the document plan tree is modified to reflect changes in complex systems' behavior over time, ensuring the output text remains current while maintaining its structured organization.
2Loss of information
If the system generates comprehensive text describing complex systems behavior, then the text provides complete situational awareness, but the text becomes large and difficult to process and update
Solution Approach 1:
The system segments the comprehensive situational awareness text into an organized document plan tree structure with hierarchical levels. This segmentation allows the system to manage large amounts of information in manageable units, making processing and updating more efficient while preserving the complete situational awareness content.
Solution Approach 2:
The system implements nesting by creating a hierarchical document plan tree structure where elements are organized in nested levels. The updated document plan tree contains nested references to both original and new data elements, allowing comprehensive information to be stored in a compact, efficiently processable format that maintains completeness while reducing processing complexity.
Data Source
AI summary
Methods, apparatuses, and computer program products are described herein that are configured to enable updating of an output text. In some example embodiments, a method is provided that comprises generating a new message for each updateable data element based on a predetermined indication. The method of this embodiment may also include determining a classification for each new message by comparing each new message with a corresponding message that describes the updateable data element. The method of this embodiment may also include generating an additional document plan tree that contains at least a portion of the new messages. The method of this embodiment may also include combining the additional document plan tree with an original document plan tree.