AI Legislative Code Validation and Style Guide Compliance

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Solution Overview

Problem

Conventional text editors and network-based systems face challenges in drafting and validating markup language code for legislative documents, particularly in conforming to style guides and applying changes from approved laws, and lack the ability to efficiently update legislative code based on new laws without natural language processing.

Innovation Solution

An artificial intelligence-based legislative code validation and publication system that uses machine learning to generate structure-based markup language code, validate it against jurisdictional style guides, and apply transformation annotations to update the code, allowing for automatic conversion and publication of updated legislative documents.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If conventional text editors are used to draft markup language code, then users can write legislative documents, but the code syntax accuracy and compliance with style guides deteriorates

Engineering Contradiction:

Improvemarkup language code syntax accuracyVSAvoiduser effort in drafting code

Core Design Contradiction:

Manufacturing precisionVSEase of operation

Solution Approach 1:

The system enables self-service by automatically generating markup language code from natural language legislative text. The AI model converts plain language input into properly formatted markup code without requiring users to manually write or validate the code syntax, thus achieving both high syntax accuracy and ease of operation

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical process of manual code writing and validation with an AI-based automated system. The machine learning model substitutes the manual mechanical effort of drafting markup language code, automatically generating syntactically correct code while maintaining ease of use through natural language input

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If manual validation of markup language code is performed, then code compliance can be checked, but the time and resources required increases

Engineering Contradiction:

Improvecode validation accuracyVSAvoidvalidation time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system implements continuous validation throughout the code generation process rather than performing discrete manual validation steps. The AI model continuously checks syntax compliance and style guide adherence during automatic code generation, ensuring reliable validation without requiring separate time-consuming manual review steps

Inventive Principle:

Principle #20Continuity of useful action

Solution Approach 2:

The patent replaces manual validation mechanics with automated AI-based validation. The machine learning model automatically validates markup language code syntax and style guide compliance, achieving high reliability while eliminating the time loss associated with manual validation processes

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Adaptability or versatility

If natural language processing methods are used to update legislative code, then the system can understand and apply changes from approved laws, but the computational complexity and processing time increases

Engineering Contradiction:

Improveability to apply changes from approved lawsVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system extracts and applies only the essential transformation rules from approved laws to update legislative code. By taking out and applying only the necessary changes rather than processing entire documents through complex NLP, the system achieves high adaptability while reducing computational complexity

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent uses parameter-based transformation rules that define specific changes to be made to legislative code. By changing parameters and applying predefined transformation patterns rather than using complex general-purpose NLP, the system achieves versatility in applying law changes while keeping the system complexity manageable

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS11042692B1Artificial intelligence-based legislative code validation and publication system

Publication Date: 2021.06.22 OPEN LAW LIBRARY

AI summary

An artificial intelligence-based legislative code validation and publication system is described herein. For example, the legislative code validation and publication system can be implemented within a user device, a network-accessible server, or a combination thereof. The legislative code validation and publication system can include a plug-in, add-on, extension, or other component that causes an enhanced text editor to support additional functionality. In particular, the plug-in causes the enhanced text editor to generate structure-based markup language code as text is entered, provide auto-complete features, and/or validate the generated structure-based markup language code according to a jurisdiction's style guide. The legislative code validation and publication system can then modify the markup language code to include codification annotations, thereby forming annotated markup language code. The legislative code validation and publication system can publish a transformed version of the annotated markup language code to cause a device to display an updated legislative code.