Skip to content

majidghassemi/Explainable-Domain-Specific-Large-Language-Models-A-Law-Case-Study

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

25 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Explainable Domain Specific Large Language Models: A Law Case Study

Final Architecture

Overview

This project introduces a pioneering framework for a question-answering system, leveraging a knowledge graph (KG) extracted from the corpus of Securities and Exchange Commission (SEC) proceedings. It aims to enhance understanding and navigation of complex legal documents.

Project Structure

  • implementation: This contains the full implementation of the system instance, showcasing the practical application of the framework.
  • evaluation: Here, various semantic evaluation methodologies are provided, demonstrating the effectiveness and accuracy of the model.
  • evaluation_helpers: Contains scripts used for generating evaluation answers from the model, crucial for validating the system's performance.
  • kg_creation: Includes scripts for creating a nested knowledge graph, along with methods for uploading it to a Neo4j database, ensuring a robust and interconnected data structure.
  • scripts/: Offers a collection of helper scripts for ontology. The ontology approach is heavily inspired by AnjaneyaTripathi's knowledge_graph.

Additional Resources

About

Explainable Domain Specific Large Language Models: A Law Case Study

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 4

  •  
  •  
  •  
  •