[ { "@id": "https://w3id.org/np/RAXDe9Lt0eqAZ5J6LYACWyeQFNmtr0-qXpOb-JPXp5Ojg/provenance", "@graph": [ { "@id": "https://w3id.org/np/RAXDe9Lt0eqAZ5J6LYACWyeQFNmtr0-qXpOb-JPXp5Ojg/assertion", "http://www.w3.org/ns/prov#wasAttributedTo": [ { "@id": "https://neverblink.eu/ontologies/llm-kg/agent" } ], "http://www.w3.org/ns/prov#wasDerivedFrom": [ { "@id": "https://doi.org/10.48550/arXiv.2403.05881" } ] } ] }, { "@id": "https://w3id.org/np/RAXDe9Lt0eqAZ5J6LYACWyeQFNmtr0-qXpOb-JPXp5Ojg/pubinfo", "@graph": [ { "@id": "https://w3id.org/np/RAXDe9Lt0eqAZ5J6LYACWyeQFNmtr0-qXpOb-JPXp5Ojg", "http://purl.org/dc/terms/created": [ { "@value": "2026-03-13T16:05:11.469Z", "@type": "http://www.w3.org/2001/XMLSchema#dateTime" } ], "http://purl.org/dc/terms/creator": [ { "@id": "https://neverblink.eu/ontologies/llm-kg/agent" } ], "http://purl.org/nanopub/x/hasNanopubType": [ { "@id": "https://neverblink.eu/ontologies/llm-kg/PaperAssessmentResult" } ], "http://purl.org/nanopub/x/supersedes": [ { "@id": "https://w3id.org/np/RAHt8HqiW8AcuusnGVccmiu6_KzjuDqksGJewBRBj6gsM" } ], "http://www.w3.org/2000/01/rdf-schema#label": [ { "@value": "LLM-KG assessment for paper 10.48550/arXiv.2403.05881" } ] }, { "@id": "https://w3id.org/np/RAXDe9Lt0eqAZ5J6LYACWyeQFNmtr0-qXpOb-JPXp5Ojg/sig", "http://purl.org/nanopub/x/hasAlgorithm": [ { "@value": "RSA" } ], "http://purl.org/nanopub/x/hasPublicKey": [ { "@value": "MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAwNz2QK3SEifno78S7+48zUB0xpTex3mAzW73ZimHqNcdEMU5/apslrGrTHGFAt/Chocgo++r6JQp5ygY7NyJHGWdaIqnt85pjX4PbNfLAvapyUO00qZP34fY61w4eZ9UMtleWEsmZKRtQPyJ8ODl46i/rfPuZlcJGpM9Nmy5mpGWuepqIEvF4a/t7pLVeCEDFSYXT+yaiygt6ynIK5f7TtEDhZpeUf/Q74WhMPJXm4yTU/hqOX4IW+50kWHNArGGZwUaXwzyG6M3Zd6UMModryGkLqS4H/MSE3ZA1Ylnms7BfWLEXhMWlaKi6HRV4nGRDLhxVSi9LSRi3LWKLhNIIQIDAQAB" } ], "http://purl.org/nanopub/x/hasSignature": [ { "@value": "WztWGY+pzNygXBhUF/SQPZ2V5JZa9avXjwhV5Z0t1R7SY9s6NG7iXcjceO23LhwmrdYtfYg/fcUZtrkKKSiRLW/8CX9NwwAp8Tb1U/0U8iHdrNha0k0CLjbYRKg2lZClcetCN2I9N/h/w1wXPVX1TeJXxS5q87IlLj8Wcy1/4yRK/ONdINpJWm6kwpJV5uQZyo1OHzxIPRAmCiU9joeoIX3cPiN2vQsGAab6PUqXYWcSmL+nM87rUMp8/5ibxjXVK1O2eLOBIEwkRLzXdDrLTGo9wqHZa6LOnPNHMtxOdFeM/74cxxbFceYdOew3mcjJSMCe26UOeTVUNuP1XIkzXg==" } ], "http://purl.org/nanopub/x/hasSignatureTarget": [ { "@id": "https://w3id.org/np/RAXDe9Lt0eqAZ5J6LYACWyeQFNmtr0-qXpOb-JPXp5Ojg" } ], "http://purl.org/nanopub/x/signedBy": [ { "@id": "https://neverblink.eu/ontologies/llm-kg/agent" } ] } ] }, { "@id": "https://w3id.org/np/RAXDe9Lt0eqAZ5J6LYACWyeQFNmtr0-qXpOb-JPXp5Ojg/Head", "@graph": [ { "@id": "https://w3id.org/np/RAXDe9Lt0eqAZ5J6LYACWyeQFNmtr0-qXpOb-JPXp5Ojg", "http://www.nanopub.org/nschema#hasAssertion": [ { "@id": "https://w3id.org/np/RAXDe9Lt0eqAZ5J6LYACWyeQFNmtr0-qXpOb-JPXp5Ojg/assertion" } ], "http://www.nanopub.org/nschema#hasProvenance": [ { "@id": "https://w3id.org/np/RAXDe9Lt0eqAZ5J6LYACWyeQFNmtr0-qXpOb-JPXp5Ojg/provenance" } ], "http://www.nanopub.org/nschema#hasPublicationInfo": [ { "@id": "https://w3id.org/np/RAXDe9Lt0eqAZ5J6LYACWyeQFNmtr0-qXpOb-JPXp5Ojg/pubinfo" } ], "@type": [ "http://www.nanopub.org/nschema#Nanopublication" ] } ] }, { "@id": "https://w3id.org/np/RAXDe9Lt0eqAZ5J6LYACWyeQFNmtr0-qXpOb-JPXp5Ojg/assertion", "@graph": [ { "@id": "https://doi.org/10.48550/arXiv.2403.05881", "http://purl.org/dc/terms/title": [ { "@value": "KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking Techniques" } ], "http://purl.org/spar/cito/describes": [ { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#KgRank" } ], "http://purl.org/spar/cito/discusses": [ { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#Almanac" }, { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#ChatEnt" } ], "@type": [ "http://www.w3.org/ns/prov#Entity" ] }, { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#KgRank", "http://purl.org/dc/terms/subject": [ { "@id": "https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMInference" } ], "@type": [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#comment": [ { "@value": "KG-Rank is an augmented LLM framework that integrates a medical Knowledge Graph (KG) with multiple ranking and re-ranking techniques to improve the factual consistency of long-form question answering in the medical domain. It works by identifying medical entities in a question, retrieving related KG triples, and then applying techniques like Similarity Ranking, Answer Expansion Ranking, and Maximal Marginal Relevance Ranking, followed by re-ranking using models like MedCPT, to refine the information provided to the LLM during inference for answer generation." } ], "http://www.w3.org/2000/01/rdf-schema#label": [ { "@value": "KG-Rank" } ], "https://neverblink.eu/ontologies/llm-kg/hasTopCategory": [ { "@id": "https://neverblink.eu/ontologies/llm-kg/top-categories#KGEnhancedLLM" } ] }, { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#Almanac", "@type": [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#comment": [ { "@value": "Almanac is discussed as previous research that leverages external medical knowledge to enhance the accuracy and reliability of LLM-generated content. It is mentioned in the introduction as a related work that attempted to address the challenge of LLM factual inconsistency, providing context for the problem KG-Rank aims to solve." } ], "http://www.w3.org/2000/01/rdf-schema#label": [ { "@value": "Almanac" } ] }, { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#ChatEnt", "@type": [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#comment": [ { "@value": "ChatENT is discussed as previous research that leverages external medical knowledge to enhance the accuracy and reliability of LLM-generated content. Similar to Almanac, it is cited in the introduction as related work demonstrating the use of external knowledge to improve LLMs, setting the stage for KG-Rank's novel approach to knowledge integration." } ], "http://www.w3.org/2000/01/rdf-schema#label": [ { "@value": "ChatENT" } ] } ] } ]