Abstract
Statement of Problem
Increasingly involved commercial contracts and long-run expectations of blockchain technology adoption require formalized and verified smart contracts (derived from legal text). Current tools suffer from issues in ambiguity detection, condition formalization, and result verification, preventing the automation and accessibility of smart contract generation.
Sources of Data
The experimental evaluation was conducted with synthetic legal contracts, mainly escrow agreements, for experimentation. The Balaji et al. legal clarity metrics [16], Legal-BERT transformer models [15] for natural language processing, and Claude AI for disambiguation were used in this research. Validation was done via wide-ranging security analysis and compilation tests of the generated smart contracts in Solidity.
Conclusions Reached
The AI-blockchain pipeline resulted in a 97.7% accuracy rate in clause classification and a 20.3% improvement in legal clarity score. The 6-step process has the potential to reduce the time required from days to just a matter of hours, with 91.4% of compilations and 100% of transactions successful. The framework shows that legal to blockchain translation while maintaining legal soundness and avoiding security vulnerabilities is possible through systematic validation strategies.