This investigation proposes the NORKE framework, a structure-aware solution for constructing KGs from normative documents that leverages the inherent normative hierarchy, to extract and formalize rules as semantically cohesive RDF triples.
A seven-stage graph-grounded pipeline that converts domain documents into a complete, auditable Web Ontology Language (OWL) Terminological Box (TBox) without any unconstrained generation step is presented, demonstrating that the pipeline produces stable, reusable domain representations from large document corpora.
Maruf Ahmed Mridul, A. Talukder, O. Seneviratne· 0 citations
An iterative, ontology-driven pipeline that transforms unstructured documents into structured, queryable knowledge graphs operating entirely on local large language models (LLMs) is presented.
Felix Neüburger, Ole Katzenberger, Salvador Cantuarias et al.· 0 citations
OaK is presented, an ontology-as-a-kernel framework that dynamically constructs and refines task-oriented ontologies for LLM agents and shows that OaK improves standard LLM agents, strengthens evidence grounding, and boosts the reliability of multi-step reasoning.
Xiaohui Zhang, Ze-Qun Sun, Cheng Yang et al.· 0 citations
A subgraph-aware semantic expansion module that coordinates $k$-hop neighborhood information with LLM-generated descriptions to alleviate structural sparsity and a contrastive ontology matching mechanism resolves structural inconsistencies by computing adaptive similarity metrics between ontology embeddings and subgrap...
Hao Li, K. Liang, Lingyuan Meng et al.· IEEE Transactions on Pattern...· 0 citations
The findings suggest that AI-based structured extraction may redefine how organisations formalise expertise, shifting from document-centric storage toward schema-driven knowledge architectures.
Dilyan Georgiev, E. Gourova· European Conference on Knowl...· 0 citations
Ontology-driven knowledge graph construction from industrial text remains challenging due to the domain specificity of documents, the scarcity of annotated resources, and the complexity of ontology engineering workflows. This paper presents and investigates the applicability of an ontology learning pipeline that combin...
Abdelhadi Belfadel, Maxence Gagnant, Joseph Kattan et al.· 0 citations
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