Towards Ontologically Grounded and Language-Agnostic Knowledge Graphs
–arXiv.org Artificial Intelligence
Knowledge graphs (KGs) have become the standard technology for the representation of factual information in applications such as recommendation engines, search, and question-answering systems. However, the continual updating of KGs, as well as the integration of KGs from different domains and KGs in different languages, remains to be a major challenge. What we suggest here is that by a reification of abstract objects and by acknowledging the ontological distinction between concepts and types, we arrive at an ontologically grounded and language-agnostic representation that can alleviate the difficulties in KG integration.
arXiv.org Artificial Intelligence
Jul-20-2023
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- Asia (0.04)
- Europe
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- United Kingdom > England
- Greater London > London (0.04)
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- Research Report (0.40)
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