The LLM-augmented KG process is structured into two principal stages: (1) synthesizing KGs by applying LLMs to perform coreference resolution, named entity recognition, and relationship extraction to relate entities from input documents; (2) performing tasks on the constructed KG using LLMs, including KG completion to fill gaps, KG question answering to query responses, and KG text generation to develop descriptions of nodes.

Authors

• Person: Not available Organization: Springer
  A survey on augmenting knowledge graphs (KGs) with large ...

Sources

• A survey on augmenting knowledge graphs (KGs) with large ... link.springer.com Springer via serper

Referenced by nodes (6)

• Large Language Models concept
• relation extraction concept
• Named Entity Recognition (NER) concept
• KGs concept
• coreference resolution concept
• LLM-enhanced KGs (LEK) concept