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Graph query languages, while precise and powerful, can sometimes be challenging to comprehend and employ. However, employing natural language to construct and query graphs presents an ideal alternative.
This approach is particularly suitable for Knowledge Graphs derived from textual data. This presentation explores the foundation, methodologies, and illustrative instances of utilizing LLMs to enhance KGs.
