Self-Aware Contract Document Generation via Entity Graphs
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Solution Overview
Problem
Current automated document authoring systems lack the ability to generate self-aware contract documents that are compliant with relevant laws, regulations, and moral standards in a timely and efficient manner, particularly in specifying relationships between entities and ensuring compliance during the authoring process.
Innovation Solution
The system employs cognitive technologies to generate self-aware contract documents by creating an entity graph and data graph data structure, which allows for the automatic generation of notifications and suggestions for compliant terms and clauses based on the entities involved, leveraging knowledge from existing documents and moral bases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated document authoring systems are used to generate contract documents, then productivity is improved, but the ability to ensure compliance with laws, regulations, and moral standards deteriorates
Solution Approach 1:
The system implements feedback mechanisms by automatically generating notifications when entities or terms violate compliance rules. The compliance checking module continuously monitors document generation processes and provides real-time feedback about potential compliance issues, allowing the system to self-correct and ensure regulatory adherence while maintaining automated document creation.
Solution Approach 2:
The patent introduces an intermediary compliance checking module that acts as a mediator between the automated document authoring system and compliance requirements. This intermediary layer validates entities, terms, and clauses against moral bases and regulatory standards, ensuring that automated generation does not compromise compliance without reducing overall productivity.
2Manufacturing precision
If cognitive technologies are used to generate self-aware contract documents with entity graphs and data graphs, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The system segments the complex document authoring process into distinct functional modules: entity graph generation, data graph creation, compliance checking, and notification generation. Each module handles a specific aspect of document creation, making the overall complex system manageable and maintainable while achieving high precision in compliance assurance through specialized processing at each stage.
Solution Approach 2:
The patent introduces new dimensional structures (entity graphs and data graphs) to represent document information. These graphical data structures add a new dimension to traditional document authoring, enabling complex relationships between entities and terms to be visualized and processed systematically, thereby improving precision without proportionally increasing operational complexity.
3Reliability
If the system generates notifications and suggestions for compliant terms, then reliability is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary compliance checking by validating entities, terms, and clauses against moral bases and regulatory standards during the document generation process itself, rather than as a separate post-processing step. This preliminary action ensures compliance is built-in from the start, reducing the need for time-consuming revisions later while maintaining high reliability.
Solution Approach 2:
The automated compliance checking system serves itself by continuously monitoring and validating its own document generation outputs. The system automatically detects compliance issues, generates notifications, and suggests corrections without requiring external manual review, thereby maintaining high compliance verification reliability while minimizing additional time requirements.
Data Source
AI summary
A method and system including a data storage device to store document files, entity graph data structures, and data graph data structures; a processor to receive input values for parameters of a plurality of entities related to a document being authored; generate an entity graph data structure linking, directly or indirectly, the plurality of entities based on shared property commonalities between the plurality of entities; generate a data graph data structure based on the entity graph data structure and at least one of at least one existing document file, curated document terms, and relevant terms acceptable to the plurality of entities; and automatically generate, based on the data graph data structure, a self-awareness notification for the document being authored, the self-awareness notification indicating an action related to a continued authoring of the document being authored; and an output to output a user interface to display the generated notification in a notification interface area of a user interface.