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{
<
https://doi.org/10.48550/arXiv.2412.05547
>
dct:title
"KG-Retriever: Efficient Knowledge Indexing for Retrieval-Augmented Large Language Models" ;
<
http://purl.org/spar/cito/describes
> <
https://neverblink.eu/ontologies/llm-kg/methods#KgRetriever
> , <
https://neverblink.eu/ontologies/llm-kg/methods#KgRetrieverEntityLevelKgConstructionUsingLlms
> ;
<
http://purl.org/spar/cito/discusses
> <
https://neverblink.eu/ontologies/llm-kg/methods#Bm25
> , <
https://neverblink.eu/ontologies/llm-kg/methods#DenseRetriever
> , <
https://neverblink.eu/ontologies/llm-kg/methods#GraphGuidedReasoning
> , <
https://neverblink.eu/ontologies/llm-kg/methods#IterRetgen
> , <
https://neverblink.eu/ontologies/llm-kg/methods#Itrg
> , <
https://neverblink.eu/ontologies/llm-kg/methods#Kgp
> , <
https://neverblink.eu/ontologies/llm-kg/methods#LlmWithCoT
> , <
https://neverblink.eu/ontologies/llm-kg/methods#NaiveLlm
> ;
a
prov:Entity
.
<
https://neverblink.eu/ontologies/llm-kg/methods#Bm25
>
a
<
http://purl.org/spar/fabio/Workflow
> ;
rdfs:label
"BM25" .
<
https://neverblink.eu/ontologies/llm-kg/methods#DenseRetriever
>
a
<
http://purl.org/spar/fabio/Workflow
> ;
rdfs:label
"DenseRetriever" .
<
https://neverblink.eu/ontologies/llm-kg/methods#GraphGuidedReasoning
>
a
<
http://purl.org/spar/fabio/Workflow
> ;
rdfs:label
"Graph-guided reasoning" .
<
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>
a
<
http://purl.org/spar/fabio/Workflow
> ;
rdfs:label
"ITER-RETGEN" .
<
https://neverblink.eu/ontologies/llm-kg/methods#Itrg
>
a
<
http://purl.org/spar/fabio/Workflow
> ;
rdfs:label
"ITRG" .
<
https://neverblink.eu/ontologies/llm-kg/methods#KgRetriever
>
dct:subject
<
https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMInference
> ;
a
<
http://purl.org/spar/fabio/Workflow
> ;
rdfs:comment
"KG-Retriever is a novel Retrieval-Augmented Generation (RAG) framework that leverages a Hierarchical Index Graph (HIG) to provide comprehensive and efficient knowledge to LLMs during the inference stage. Its goal is to improve the quality, credibility, and efficiency of LLM-generated responses by addressing challenges like multi-hop question answering and information fragmentation. This directly aligns with using KGs to enhance LLM performance during inference." ;
rdfs:label
"KG-Retriever" ;
<
https://neverblink.eu/ontologies/llm-kg/hasTopCategory
> <
https://neverblink.eu/ontologies/llm-kg/top-categories#KGEnhancedLLM
> .
<
https://neverblink.eu/ontologies/llm-kg/methods#KgRetrieverEntityLevelKgConstructionUsingLlms
>
dct:subject
<
https://neverblink.eu/ontologies/llm-kg/categories#LLMAugmentedKGConstruction
> ;
a
<
http://purl.org/spar/fabio/Workflow
> ;
rdfs:comment
"This method describes the specific use of large language models (Qwen-72B) with in-context learning and designed prompts to extract entities and relations from unstructured text within documents. This process is crucial for constructing the entity-level knowledge graph layer of the Hierarchical Index Graph within the KG-Retriever framework, directly using LLMs to perform a core KG construction task." ;
rdfs:label
"KG-Retriever's Entity-Level KG Construction using LLMs" ;
<
https://neverblink.eu/ontologies/llm-kg/hasTopCategory
> <
https://neverblink.eu/ontologies/llm-kg/top-categories#LLMAugmentedKG
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<
https://neverblink.eu/ontologies/llm-kg/methods#Kgp
>
a
<
http://purl.org/spar/fabio/Workflow
> ;
rdfs:label
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>
a
<
http://purl.org/spar/fabio/Workflow
> ;
rdfs:label
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<
https://neverblink.eu/ontologies/llm-kg/methods#NaiveLlm
>
a
<
http://purl.org/spar/fabio/Workflow
> ;
rdfs:label
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