Ontology-Aware LLMs for Human-Usable Knowledge Graph Systems
Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence. Doctoral Consortium. Pages 8325-8326.
https://doi.org/10.24963/ijcai.2026/941
Keywords
- Humans and AI: Intelligent user interfaces
- Knowledge Representation and Reasoning: Semantic Web
- Natural Language Processing: Language models
Abstract
Knowledge graphs (KGs) promise machine-readable semantics together with human-readable labels and relations, yet domain experts struggle to use them due to technical barriers, especially in automatically constructed graphs with unlabeled nodes and complex connections. While LLMs enable KG interfaces such as retrieval-augmented generation, their potential to leverage ontology definitions to improve graph readability remains unexplored. This research investigates LLMs as ontology-aware verbalization interfaces that generate human-readable and usable textual information encoded in the KG structure.
@inproceedings{ijcai2026p941,
title = {Ontology-Aware LLMs for Human-Usable Knowledge Graph Systems},
author = {do Valle Miranda, Luiz},
booktitle = {Proceedings of the Thirty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-26}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Diego Calvanese},
pages = {8325--8326},
year = {2026},
month = {8},
note = {Doctoral Consortium},
doi = {10.24963/ijcai.2026/941},
url = {https://doi.org/10.24963/ijcai.2026/941},
}
TY - CPAPER TI - Ontology-Aware LLMs for Human-Usable Knowledge Graph Systems AU - do Valle Miranda, Luiz T2 - Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2026 SP - 8325 EP - 8326 DO - 10.24963/ijcai.2026/941 UR - https://doi.org/10.24963/ijcai.2026/941 ER -Copied
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