Logical English LLM Hybrid System
This research project is centred on developing a groundbreaking hybrid system that integrates large language models (LLMs) with a Prolog reasoning engine and controlled natural language processing (specifically Logical English) to transform complex tax legislation into computable contracts. The main goals of the project include enhancing the efficiency and accuracy of legal document processing, which currently involves time-consuming manual interpretation and conversion.
Key Objectives:
- System Integration: Seamlessly combine LLMs for natural language processing, Logical English for structured language translation, and Prolog for logical reasoning to create a unified system capable of handling the intricacies of tax legislation.
- Increase Efficiency: Significantly reduce the time required to convert tax legislation into computable formats compared to traditional methods.
- Improve Accuracy: Ensure the system maintains high legal integrity in its outputs, making them reliable for professional use.
Innovative Aspects:
- Technological Synergy: The project explores the novel integration of different AI technologies, each with distinct functionalities—LLMs for parsing text, Logical English for reducing ambiguity, and Prolog for executing logical operations based on the structured input.
- Adaptive Learning: Incorporate mechanisms for the system to learn from feedback and corrections, enhancing its performance over time.
- Human-AI Interaction: Develop interfaces that facilitate effective collaboration between human experts and the AI system, improving the system’s outputs through human insights.
Expected Outcomes:
- New Integration Techniques: Develop methodologies for effectively combining technologies that have not traditionally been used together.
- Controlled Natural Language Enhancements: Advance the capabilities of controlled natural language systems in handling legal language, setting a new standard for accuracy and reliability.
- Frameworks for Human-AI Collaboration: Establish models and interfaces that optimize the contribution of human expertise to AI processes.
Potential Impact:
- Legal and Regulatory Fields: The system aims to revolutionize how legal documents are processed, offering significant improvements in speed and accuracy that could greatly benefit legal professionals and regulatory bodies.
- Broader AI Applications: Insights from this project could inform AI applications in other domains where complex document processing is required, promoting broader technological advancements.
This research represents a substantial step forward in the application of AI technologies to legal document processing, combining cutting-edge AI capabilities with the precision required for legal compliance and functionality. The project not only aims to enhance current practices but also contributes to the body of knowledge in AI, legal technology, and hybrid systems development.
