This repository provides a knowledge-graph–oriented variant of Meta-Llama-3-8B-Instruct, fine-tuned with LoRA on the T-REx factual triple dataset as a triple extraction model.
The model takes natural language passages as input and outputs factual (head, relation, tail) triples in a structured JSON format, designed to be used as a knowledge graph backend for RAG systems (e.g., HippoRAG-style KG retrieval).
Training Details
Data
Source: T-REx factual triple dataset
Preprocessing (conceptual):
T-REx triples (subject, relation, object) were converted into simple natural language sentences.
The model was supervised to recover the triples in a structured JSON format:
