KGCP/paper2lkg
A Local Knowledge Graph Construction (KGC) pipeline designed to transform individual academic papers into their structured local Knowledge Graph (KG) representations. The pipeline leverages Large Language Models (LLMs), particularly generative LLMs, to automate key Natural Language Processing (NLP) tasks in KGC.
This tool helps researchers and knowledge managers convert individual academic papers into structured local Knowledge Graphs. You input PDF research papers, and it outputs a graph database representation of the paper's key entities, relationships, and concepts. It's designed for anyone needing to extract and organize information from academic literature systematically.
Use this if you need to automatically extract structured information from research papers to build a navigable knowledge base or integrate findings across multiple documents.
Not ideal if you're looking for a tool to summarize papers, perform full-text search, or analyze vast collections of documents without building structured knowledge graphs.
Stars
11
Forks
1
Language
Python
License
MIT
Category
Last pushed
Feb 06, 2026
Commits (30d)
0
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