8 citations · 12 across the 9 of their papers we have counts for
10 papers
Walking on the DARKSIDE
Aldo Gangemi, Emanuele Bottazzi
Large Language Models (LLMs) do not natively track the path of exclusions that a coherent discourse demands. When an input rests on a fabricated authority, a misapplied mechanism,…
OntoExtend: A Framework for Requirement-driven and Scalable Ontology Extension with LLMs
Anna Sofia Lippolis, Mohammad Javad Saeedizade, Stefan Schmid +5
Ontology extension refers to the process of enriching an existing ontology in response to emerging requirements, making it more complete. This task is a resource-intensive and erro…
When CQs Go Wrong: Challenges in CQ Verification with OE-Assist
Anna Sofia Lippolis, Mohammad Javad Saeedizade, Robin Keskisärkkä +3
Competency Questions (CQs) are the central component of CQ-verification, an established process in which an ontology is evaluated against a set of natural language questions to det…
Tacit Knowledge Extraction via Logic Augmented Generation and Active Inference
Lorenzo Lamazzi, Aldo Gangemi, Alessio Giberti +4
Tacit knowledge plays a central role in human expertise, yet it remains difficult to capture, formalize, and reuse in machine-interpretable form. This challenge is especially relev…
The Medical Metaphors Corpus (MCC)
Anna Sofia Lippolis, Andrea Giovanni Nuzzolese, Aldo Gangemi
Metaphor is a fundamental cognitive mechanism that shapes scientific understanding, enabling the communication of complex concepts while potentially constraining paradigmatic think…
Large Language Models Assisting Ontology Evaluation
Anna Sofia Lippolis, Mohammad Javad Saeedizade, Robin Keskisärkkä +3
Ontology evaluation through functional requirements, such as testing via competency question (CQ) verification, is a well-established yet costly, labour-intensive, and error-prone…
Assessing the Capability of Large Language Models for Domain-Specific Ontology Generation
Anna Sofia Lippolis, Mohammad Javad Saeedizade, Robin Keskisarkka +3
Large Language Models (LLMs) have shown significant potential for ontology engineering. However, it is still unclear to what extent they are applicable to the task of domain-specif…
Enhancing multimodal analogical reasoning with Logic Augmented Generation
Anna Sofia Lippolis, Andrea Giovanni Nuzzolese, Aldo Gangemi
Recent advances in Large Language Models have demonstrated their capabilities across a variety of tasks. However, automatically extracting implicit knowledge from natural language…
Ontology Generation using Large Language Models
Anna Sofia Lippolis, Mohammad Javad Saeedizade, Robin Keskisärkkä +5
The ontology engineering process is complex, time-consuming, and error-prone, even for experienced ontology engineers. In this work, we investigate the potential of Large Language…
Logic Augmented Generation
Aldo Gangemi, Andrea Giovanni Nuzzolese
Semantic Knowledge Graphs (SKG) face challenges with scalability, flexibility, contextual understanding, and handling unstructured or ambiguous information. However, they offer for…