Semantic Reasoning for Device Identification in Dynamic Internet of Things Environments with Large Language Models

Gui Z, Kuty L, Schraudner D, Harth A (2026)

Publication Type: Conference contribution

Publication year: 2026

Journal

Lecture Notes in Computer Science Springer Verlag

Publisher: Springer Science and Business Media Deutschland GmbH

Book Volume: 15836 LNCS

Pages Range: 335-349

Conference Proceedings Title: Lecture Notes in Computer Science

Event location: Kanazawa JP

ISBN: 9783031971402

DOI: 10.1007/978-3-031-97141-9_23

Abstract

This work evaluates the capabilities of Large Language Models (LLMs) in semantic reasoning tasks. We construct a knowledge graph that represents a real-world Internet of Things (IoT) environment and define various reasoning rules for device identification use cases. We test the performance of three LLMs: Llama-3.1, Qwen-2.5, GPT-4o, based on different levels of fine-grained rule descriptions in the input context and the increasing rule complexity. We use a rule-based reasoner, Apache Jena, to generate the ground truth data for each reasoning rule. The results show that while LLMs are effective in retrieving direct links in the knowledge graph, they struggle with highly customized, complex reasoning rules involving multiple triple patterns. This work provides an application and a baseline for using LLMs to enable semantic reasoning for device identification in IoT environments.

Authors with CRIS profile

Zhou Gui Lehrstuhl für Wirtschaftsinformatik, insbesondere Technische Informationssysteme Daniel Schraudner Lehrstuhl für Wirtschaftsinformatik, insbesondere Technische Informationssysteme Andreas Harth Lehrstuhl für Wirtschaftsinformatik, insbesondere Technische Informationssysteme

How to cite

APA:

Gui, Z., Kuty, L., Schraudner, D., & Harth, A. (2026). Semantic Reasoning for Device Identification in Dynamic Internet of Things Environments with Large Language Models. In Ryutaro Ichise (Eds.), Lecture Notes in Computer Science (pp. 335-349). Kanazawa, JP: Springer Science and Business Media Deutschland GmbH.

MLA:

Gui, Zhou, et al. "Semantic Reasoning for Device Identification in Dynamic Internet of Things Environments with Large Language Models." Proceedings of the 30th International Conference on Natural Language and Information Systems, NLDB 2025, Kanazawa Ed. Ryutaro Ichise, Springer Science and Business Media Deutschland GmbH, 2026. 335-349.

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