61 citations · 142 across the 17 of their papers we have counts for
9 papers · 1 filter
LLMs4Life: Large Language Models for Ontology Learning in Life Sciences
Nadeen Fathallah, Steffen Staab, Alsayed Algergawy
Ontology learning in complex domains, such as life sciences, poses significant challenges for current Large Language Models (LLMs). Existing LLMs struggle to generate ontologies wi…
F -- A Model of Events based on the Foundational Ontology DOLCE+DnS Ultralite
Ansgar Scherp, Thomas Franz, Carsten Saathoff +1
The lack of a formal model of events hinders interoperability in distributed event-based systems. In this paper, we present a formal model of events, called Event-Model-F. The mode…
Generating Ontologies via Knowledge Graph Query Embedding Learning
Yunjie He, Daniel Hernandez, Mojtaba Nayyeri +4
Query embedding approaches answer complex logical queries over incomplete knowledge graphs (KGs) by computing and operating on low-dimensional vector representations of entities, r…
eSPARQL: Representing and Reconciling Agnostic and Atheistic Beliefs in RDF-star Knowledge Graphs
Xinyi Pan, Daniel Hernández, Philipp Seifer +2
Over the past few years, we have seen the emergence of large knowledge graphs combining information from multiple sources. Sometimes, this information is provided in the form of as…
Predictive Multiplicity of Knowledge Graph Embeddings in Link Prediction
Yuqicheng Zhu, Nico Potyka, Mojtaba Nayyeri +4
Knowledge graph embedding (KGE) models are often used to predict missing links for knowledge graphs (KGs). However, multiple KG embeddings can perform almost equally well for link…
Shrinking Embeddings for Hyper-Relational Knowledge Graphs
Bo Xiong, Mojtaba Nayyer, Shirui Pan +1
Link prediction on knowledge graphs (KGs) has been extensively studied on binary relational KGs, wherein each fact is represented by a triple. A significant amount of important kno…