Accelerating Knowledge Graph and Ontology Engineering with Large Language Models

Cogan Shimizu, Pascal Hitzler
11/14/2024
cs.AI

No confident code implementation found for this paper. 2 possible matches can be shown below.

Abstract

Large Language Models bear the promise of significant acceleration of key Knowledge Graph and Ontology Engineering tasks, including ontology modeling, extension, modification, population, alignment, as well as entity disambiguation. We lay out LLM-based Knowledge Graph and Ontology Engineering as a new and coming area of research, and argue that modular approaches to ontologies will be of central importance.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 2 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Using Large Language Models for OntoClean-based Ontology Refinement

80% match2024

LLMs4Life: Large Language Models for Ontology Learning in Life Sciences

80% match1 repo52024

OntoLearner: A Modular Python Library for Ontology Learning with Large Language Models

80% match1 repo532026

GenOM: Ontology Matching with Description Generation and Large Language Model

80% match2025

Can Large Language Models Augment a Biomedical Ontology with missing Concepts and Relations?

80% match2023

Large Language Models for Scholarly Ontology Generation: An Extensive Analysis in the Engineering Field

80% match1 repo52024

Cite this paper

@article{shimizu2024accelerating,
  title  = {Accelerating Knowledge Graph and Ontology Engineering with Large Language Models},
  author = {Cogan Shimizu and Pascal Hitzler},
  year   = {2024},
  eprint = {2411.09601},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2411.09601v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2411.09601.svg)](https://codeofpaper.com/paper/2411.09601)

Discussion