The First Workshop on LLM-driven Knowledge Graph and Ontology Engineering (llms4kgoe) focuses on the rapidly evolving intersection of Large Language Models (LLMs), semantic technologies, and ontology engineering. It addresses challenges and opportunities in leveraging LLMs for ontology creation, refinement, and validation, covering both theoretical and practical aspects such as automated ontology generation pipelines, evaluation methodologies, hallucination mitigation, and ensuring semantic consistency. The workshop provides a venue to discuss methods, evaluation techniques, and best practices for this emerging paradigm.

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:

• Full papers should describe a well-motivated problem, position it in existing work, present the proposed method or system with enough detail to understand and reasonably reproduce it, and support its claims with a thorough set of experiments or analyses plus a short reflection on limitations and implications. Length of full papers should be between 10-12 pages (CEUR Style). 
• Short Papers should describe one focused idea or preliminary result, explain why it is interesting, outline the core approach or insight without exhaustive technical detail, and provide enough empirical or analytical evidence to make the contribution credible. Length of Short papers should be 6 pages (CEUR style).

List of Topics

• LLM-to-KG with schema/pattern constraints

• Education & UX for CQ/axiom authoring

• Evidence-linked triple extraction and provenance

• Hallucination benchmarking: metrics and datasets

• Post-hoc KG repair with reasoners or learned validators

• Calibration and abstention for link prediction and typing

• Robustness and red-teaming for KG extraction

• Domain-specific KG applications (biomedical, climate, materials science, etc.)

• Lifecycle & Maintenance of ontologies with LLMs

• Modular Evaluation & Benchmarks

• Provenance & Governance in ontology workflows

• Neuro-symbolic control (SHACL/OWL-guided generation, reasoner-in-the-loop)

• Human-in-the-loop protocols

• Domain adaptation & continual learning

• Multilingual & multimodal ontology engineering

• Operational efficiency metrics

• Standards & community alignment (FAIR, OBO, ODP, OAEI, LLMs4OL)

Committees

Program Committee

• Shreyas Casturi, Wright State University

• Antrea Christou, Wright State University

• Nirmal Gelal, Kansas State University

• Yinglun Zhang, Kansas State University

• Soheil Abadifard, Kansas State University

• Aryan Dalal, Kansas State University

• Kathleen Jagodnik, Kansas State University

• Elham Ghiasi, Wright State University

• Chris Davis Jaldi, Wright State University

• Michael McCain, Wright State University

• Anmol Saini, Wright State University

• Susan Shrestha, Wright State University

Organizing committee

• Aryan Singh Dalal, Kansas State University

• Kathleen Jagodnik, Kansas State University

• Hande McGinty, Kansas State University

• Cogan Shimizu, Wright State University

• Maria Maleshkova, Helmut Schmidt University

Publication

llms4kgoe 2026 proceedings will be published by CEUR. Authors are advised to Follow the CEUR 

Venue

In-person, co-located with ESWC 2026

Contact

All questions about submissions should be emailed to aryand@ksu.edu