Summary of Ontology-grounded Automatic Knowledge Graph Construction by Llm Under Wikidata Schema, By Xiaohan Feng et al.

Ontology-grounded Automatic Knowledge Graph Construction by LLM under Wikidata schema

by Xiaohan Feng, Xixin Wu, Helen Meng

First submitted to arxiv on: 30 Dec 2024

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Summary difficulty	Written by	Summary
High	Paper authors	High Difficulty Summary Read the original abstract here
Medium	GrooveSquid.com (original content)	Medium Difficulty Summary This paper proposes an ontology-grounded approach to constructing Knowledge Graphs (KGs) using Large Language Models (LLMs). The authors generate Competency Questions (CQs) on a knowledge base to discover the scope of knowledge, extract relations from CQs, and replace equivalent relations with their counterparts in Wikidata. To ensure consistency and interpretability in the resulting KG, the authors ground generation with the authored ontology based on extracted relations. The approach is evaluated on benchmark datasets, demonstrating competitive performance in the knowledge graph construction task.
Low	GrooveSquid.com (original content)	Low Difficulty Summary This paper shows how to use special language models to build a map of knowledge called a Knowledge Graph (KG). They ask questions about what we know and use that information to create connections between ideas. To make sure the KG makes sense, they match it with an organized plan or “ontology”. This helps keep the KG organized and easy to understand. The results are very good and show promise for building large KGs quickly without needing a lot of human help.