Natural Language Generation Document Plan Schema
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Solution Overview
Problem
Conventional natural language generation systems face limitations in flexibility and computational efficiency when structuring documents, as they either rely on static pre-defined plans or exhaustive searches, which are not suitable for generating text in multiple different circumstances.
Innovation Solution
A method that combines static and dynamic document structuring techniques by using a schema to specify a first set of rhetorical relations and identifying a second set based on metadata, allowing for the generation of a document plan that is both flexible and computationally efficient.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If static pre-defined document plans are used, then computational efficiency is maintained, but flexibility and adaptability to different circumstances deteriorate
Solution Approach 1:
The system dynamically selects and combines rhetorical relations based on metadata associated with content items, transforming the static document planning process into a dynamic one that adapts to different circumstances while maintaining computational efficiency through guided selection rather than exhaustive search
Solution Approach 2:
The system changes the parameters of document structuring by using metadata attributes (such as importance, type, and context) to determine which rhetorical relations to apply, allowing the same content to be structured differently based on varying parameters without requiring exhaustive exploration of all possible structures
2Adaptability or versatility
If exhaustive search methods are used for document structuring, then flexibility and adaptability are improved, but computational efficiency deteriorates
Solution Approach 1:
The system performs preliminary action by pre-defining a schema of valid rhetorical relations and their constraints before the actual document generation process. This preliminary structuring guides the subsequent selection process, eliminating the need for exhaustive search while maintaining flexibility through the pre-established framework of valid relations
Solution Approach 2:
The system segments the document structuring process into distinct phases: schema definition, metadata analysis, and rhetorical relation selection. This segmentation allows the system to leverage the schema for efficient guidance while using metadata-driven selection for adaptability, avoiding the need for a single exhaustive search process
3Adaptability or versatility
If dynamic metadata-based rhetorical relation identification is used, then adaptability to various contexts is improved, but device complexity increases
Solution Approach 1:
The system introduces a schema as an intermediary between the metadata and the rhetorical relation selection process. This intermediary translates complex metadata information into structured constraints that guide relation selection, reducing the direct complexity of interpreting metadata while maintaining adaptability through the metadata-driven approach
Data Source
AI summary
Techniques for use in connection with generating text, the techniques comprise: obtaining a plurality of items of content and associated metadata; and generating a document plan comprising a plurality of rhetorical relations among items of content in the plurality of items of content, the plurality of rhetorical relations comprising a first set of one or more rhetorical relations and a second set of one or more rhetorical relations different from the first set, the generating comprising: obtaining a schema specifying the first set of one or more rhetorical relations; and identifying the second set of rhetorical relations based, at least in part, on the associated metadata, wherein the second set of rhetorical relations is not in the schema.