arXiv:2606. 20691v1 Announce Type: cross Abstract: Ontologies are useful structures to organize and maintain information that can be understood both by humans and systems.
arXiv:2608.22974v1 Announce Type: new Abstract: Large language model (LLM) agents rely heavily on knowledge encoded in model parameters or presented as unstructured context. In domain-specific tasks,...
arXiv:2610.01393v1 Announce Type: cross Abstract: Constructing typed, justified semantic links between ontologies is essential for enabling interoperability across heterogeneous and interdisciplinary...
arXiv:2607. 01977v1 Announce Type: new Abstract: Ontology learning (OL) aims to automatically construct structured knowledge models from text, yet progress remains fragmented across methods, domains, and evaluation practices.
arXiv:2607. 24551v1 Announce Type: new Abstract: Maintenance regulations are complex legal texts that are difficult to exploit when addressing a specific case and challenging to integrate into operational systems.
arXiv:2607. 24784v1 Announce Type: new Abstract: Specialised translation relies on the use of documentary and terminological resources, including corpora.
arXiv:2507. 21438v2 Announce Type: replace Abstract: Ontologies and knowledge graphs require continuous evolution to remain comprehensive and accurate, but manual curation is labor intensive.
arXiv:2608.31118v1 Announce Type: new Abstract: The effect of Large Language Model (LLM) scale on ontology learning (OL) performance remains insufficiently characterized. We present a controlled eval...
arXiv:2607. 17963v1 Announce Type: new Abstract: Ontology extension refers to the process of enriching an existing ontology in response to emerging requirements, making it more complete.
arXiv:2605. 22093v3 Announce Type: replace Abstract: Knowledge graphs have become the primary vehicle for data integration and are critical to the success of modern AI, but the diversity of KG modelling practices, from lightweight vocabularies to richly axiomatised ontologies, makes integration and reuse expensive and brittle.
arXiv:2605. 28965v2 Announce Type: replace Abstract: Linking free-text phenotype descriptions to ontology terms, typically referred to as phenotype annotation, is essential for the cross-study integration of comparative morphological data.
arXiv:2607. 16201v1 Announce Type: new Abstract: Ontology engineering remains a critical bottleneck in knowledge-intensive AI systems.
arXiv:2609.14652v1 Announce Type: cross Abstract: Large Language Model (LLM) applications often transfer domain concepts into the model's context informally, through prompt prose, schema dumps, and e...