Using LLMs as Ontology Engineers: Methods, Workflows, and Pitfalls
type: Nanopublication
has assertion: assertion
has provenance: provenance
has publication info: pubinfo
created: 2026-08-31T09:54:59Z
creator: event-bot
license: https://creativecommons.org/licenses/by/4.0/
introduces: Using LLMs as Ontology Engineers: Methods, Workflows, and Pitfalls
was created from template: workshop-template

sig
has algorithm: RSA
signed by: Tobias Kuhn

Using LLMs as Ontology Engineers: Methods, Workflows, and Pitfalls
type: Event
type: Space
type: Tutorial
description: Generative AI is transforming ontology engineering. Large Language Models (LLMs) can assist with tasks such as terminology extraction, concept discovery, taxonomy construction, relationship identification, ontology documentation, and ontology alignment, significantly accelerating the development of semantic models. At the same time, AI-generated ontologies often contain conceptual inconsistencies, incorrect abstractions, hidden assumptions, and other modeling errors that require careful human review. This hands-on tutorial explores how generative AI can be effectively integrated into the ontology engineering lifecycle. Through demonstrations and practical exercises, participants will learn how to use LLMs to support and accelerate ontology development, recognize common failure modes, and apply established semantic modeling principles to validate and improve AI-generated artifacts.
end date: 2026-09-15T17:30:00+02:00
location: Suite +1
start date: 2026-09-15T16:00:00+02:00
has admin: Daniel Mietchen
has admin: Tobias Kuhn
has admin: event-bot
is sub space of: 2026-eu