NLP Smart Contract Generation for Flexible Chaincode Assembly
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Solution Overview
Problem
Existing contract enforcement mechanisms, especially in multiple-party and cross-jurisdictional contexts, are costly and impractical, and smart contracts on distributed ledgers are irreversible and lack flexibility.
Innovation Solution
A system utilizing natural language processing (NLP) to extract contract terms and generate chaincodes for smart contracts, enabling automatic execution on blockchain platforms, with reinforcement learning for accuracy and flexibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional contract enforcement mechanisms are used, then legal redress can be sought, but enforcement costs are high and the process is impractical
Solution Approach 1:
The patent replaces traditional mechanical legal enforcement systems with an automated smart contract execution system on blockchain. The smart contract automatically enforces agreement terms through predefined conditions and actions, eliminating the need for costly court proceedings and manual enforcement while maintaining reliability through cryptographic verification and decentralized consensus.
2Productivity
If smart contracts on distributed ledgers are used, then automatic execution is achieved, but the contracts are irreversible and lack flexibility
Solution Approach 1:
The patent introduces dynamic elements to smart contracts by implementing upgradeable contract structures and governance mechanisms that allow modifications after deployment. The system enables contract parameters to be adjusted and terms to be updated through authorized parties or governance votes, transforming static irreversible contracts into flexible, adaptable agreements that can respond to changing conditions while maintaining automatic execution capabilities.
3Productivity
If natural language processing is used to generate smart contracts, then contract generation efficiency is improved, but accuracy of chaincode generation must be ensured
Solution Approach 1:
The patent implements feedback mechanisms in the NLP-based smart contract generation system by incorporating validation layers that verify generated chaincode against the original natural language terms. The system uses confirmation prompts for critical terms, allows user review and correction of generated code, and employs testing frameworks to validate contract behavior, ensuring high accuracy while maintaining generation efficiency through automated processing.
Data Source
AI summary
A system for generating smart contracts may include a first subsystem to receive a written or verbal contract, and a second subsystem to identify terms of the contract using natural language processing (NLP). The system may additionally include a third subsystem to correlate processed NLP terms of the contract with chaincode in a library, and a fourth subsystem to combine correlated NLP terms to generate a smart contract. Methods of generating a smart contract may include inputting natural language contract terms into a smart contract generation system and identifying the natural language contract terms with a natural language processing system. The method may further include correlating at least some of the contract terms to chaincodes stored in a library, generating chaincodes for any contract terms that do not correlate to any chaincodes stored in the library, and assembling the chaincodes into a smart contract.