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.

38
/ 100
Emerging

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.

academic-research knowledge-management literature-review information-extraction scientific-data-organization
No Package No Dependents
Maintenance 10 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 7 / 25

How are scores calculated?

Stars

11

Forks

1

Language

Python

License

MIT

Last pushed

Feb 06, 2026

Commits (30d)

0

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