Matches in Nanopublications for { ?s ?p ?o <https://w3id.org/np/RAyPwIY08n2V19BEVLAKSCBErCESqc20Z0tPUqucIHetY/assertion>. }
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- arXiv.2512.19092 type Entity assertion.
- BetaE type Workflow assertion.
- CQD type Workflow assertion.
- GQE type Workflow assertion.
- Query2Box type Workflow assertion.
- ROG type Workflow assertion.
- BetaE label "BetaE" assertion.
- CQD label "CQD" assertion.
- GQE label "GQE" assertion.
- Query2Box label "Query2Box" assertion.
- ROG label "ROG (Reasoning Over knowledge Graphs with large language models)" assertion.
- ROG comment "ROG is a framework designed to improve complex logical reasoning over knowledge graphs using LLMs. It achieves this by decomposing FOL queries, retrieving query-relevant subgraphs, and employing LLM-based chain-of-thought reasoning to answer these queries step-by-step. The method directly enhances a KG task (answering complex logical queries) by leveraging LLM capabilities." assertion.
- arXiv.2512.19092 describes ROG assertion.
- arXiv.2512.19092 discusses BetaE assertion.
- arXiv.2512.19092 discusses CQD assertion.
- arXiv.2512.19092 discusses GQE assertion.
- arXiv.2512.19092 discusses Query2Box assertion.
- ROG subject LLMAugmentedKGQuestionAnswering assertion.
- arXiv.2512.19092 title "A Large Language Model Based Method for Complex Logical Reasoning over Knowledge Graphs" assertion.
- ROG hasTopCategory LLMAugmentedKG assertion.