Narrative Extraction with GenAI: Human-centric Knowledge Graph Creation from Text

In a world overflowing with unstructured data, from emails and reports to PDFs and legal documents, transforming this textual overload into actionable knowledge is more urgent than ever.

This session explores how the fusion of GenAI and graph technology can reveal the stories hidden deep within complex text. We’ll dive into a powerful process that mimics human reasoning, identifying facts, events, and relationships in natural language, and transforming them into rich, queryable graph structures.

You’ll discover how to specify custom entities and relationships using one-shot prompting, and how to normalise them into a coherent graph. We’ll also showcase a human-in-the-loop process that empowers analysts to verify, refine, or discard extracted content with just a few clicks, ensuring quality, relevance, and trust in the resulting knowledge graph.

By combining the contextual power of GenAI with the structural clarity of graphs, this presentation will demonstrate how unstructured documents can evolve into dynamic knowledge networks, ready to power smarter systems and decisions.

Speaker: Federica Ventruto

Resources:
Get Started with Aura – https://bit.ly/3LOLrjh
Deployment Center – https://bit.ly/4jOelM3
Ground AI Systems and Agents with Neo4j – https://bit.ly/4oVsnyb

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