Systeme und Verfahren zur Ontologieorientierten Grafikdatensatzmodellierung, Datenabruf und Hybridstrukturierung Generativer Künstlicher Intelligenzausgänge

Details

Veröffentlichungs-Nr.

EP4818922

Anmeldetag

3. April 2025

Veröffentlichung

7. Oktober 2026

Rechtsraum

EP

Abstract

The present disclosure relates to systems and methods for ontology-oriented graph dataset modeling, data retrieval, and hybrid structuring of generative machine learning outputs, which address the challenges of querying and extracting clinical insights from large, complex datasets. By combining knowledge graphs and large language models, embodiments of the present disclosure enable lay users to perform natural language queries on large, structured datasets and receive evidence-backed results with visual context. Embodiments include an orchestrator module powered by one or more LLMs and an instruction prompt, which selects an appropriate context retrieval tool based on a user's query. The context retrieval tool retrieves results from an ontologically-oriented graph, generates a knowledge graph, and provides a response to the query. This approach improves the efficiency and accuracy, allowing users to discover novel and unknown relationships within the dataset without needing comprehensive schema knowledge, thereby overcoming the high barrier of entry for extracting insights.

Anmelder

Firma

Koninklijke Philips N.V.

Land

🇳🇱 Niederlande