KGGen: Advancing Knowledge Graph Extraction with Language Models and Clustering Techniques – #CryptoUpdatesGNIT

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KGGen: Advancing Knowledge Graph Extraction with Language Models and Clustering Techniques – #CryptoUpdatesGNIT

Knowledge graphs (KGs) are the foundation of artificial intelligence applications but are incomplete and sparse, affecting their effectiveness. Well-established KGs such as DBpedia and Wikidata lack essential entity relationships, diminishing their utility in retrieval-augmented generation (RAG) and other machine-learning tasks. Traditional extraction methods are likely to provide sparse graphs with absent important connections or noisy, redunda…