https://m.youtube.com/playlist?list=PLGtYdYqSoNFD5BAUcc5dIeXoGPl1EgPXB
📚 Part of the “Knowledge Graphs & GraphRAG” series.
In this chapter, we explore how Large Language Models (LLMs) can be used as intelligent Knowledge Graph Builders — automatically extracting entities, identifying relationships, and populating graph schemas from raw unstructured text.
🔍 What you'll learn:
✅ How LLMs perform Named Entity Recognition (NER) for KG construction
✅ Relation extraction and triple generation using LLMs
✅ Schema-guided vs. schema-free KG population strategies
✅ Integrating LLM-built graphs into GraphRAG pipelines
✅ Practical patterns with Neo4j and LangChain
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