[ { "@graph" : [ { "@id" : "https://w3id.org/np/RAjG98Gpzlzwiy3i6yP7Fj1wTHVecNCfQVG0TPWBBT9uc", "@type" : [ "http://www.nanopub.org/nschema#Nanopublication" ], "http://www.nanopub.org/nschema#hasAssertion" : [ { "@id" : "https://w3id.org/np/RAjG98Gpzlzwiy3i6yP7Fj1wTHVecNCfQVG0TPWBBT9uc/assertion" } ], "http://www.nanopub.org/nschema#hasProvenance" : [ { "@id" : "https://w3id.org/np/RAjG98Gpzlzwiy3i6yP7Fj1wTHVecNCfQVG0TPWBBT9uc/provenance" } ], "http://www.nanopub.org/nschema#hasPublicationInfo" : [ { "@id" : "https://w3id.org/np/RAjG98Gpzlzwiy3i6yP7Fj1wTHVecNCfQVG0TPWBBT9uc/pubinfo" } ] } ], "@id" : "https://w3id.org/np/RAjG98Gpzlzwiy3i6yP7Fj1wTHVecNCfQVG0TPWBBT9uc/Head" }, { "@graph" : [ { "@id" : "https://doi.org/10.48550/arXiv.2410.04949", "@type" : [ "http://www.w3.org/ns/prov#Entity" ], "http://purl.org/dc/terms/title" : [ { "@value" : "Leverage Knowledge Graph and Large Language Model for Law Article Recommendation: A Case Study of Chinese Criminal Law" } ], "http://purl.org/spar/cito/describes" : [ { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#CLAKGLLMRecommendationFramework" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#LLMbasedCLAKGConstruction" } ], "http://purl.org/spar/cito/discusses" : [ { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#BERT" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#DPCNN" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GRU" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GraphRAG" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#LightRAG" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#RGCN" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#TFIDFRAG" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#BERT", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "BERT" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#CLAKGLLMRecommendationFramework", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://purl.org/dc/terms/subject" : [ { "@id" : "https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMInference" } ], "http://www.w3.org/2000/01/rdf-schema#comment" : [ { "@value" : "This closed-loop framework leverages the Case-Enhanced Law Article Knowledge Graph (CLAKG) to ground the recommendations generated by an LLM during the inference stage. By retrieving relevant historical case information and candidate law articles from the CLAKG, the framework enables the LLM to provide more accurate law article recommendations and effectively mitigates issues like hallucinations in LLM outputs, thereby enhancing LLM performance." } ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "CLAKG-LLM Law Article Recommendation Framework" } ], "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#DPCNN", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "DPCNN" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GRU", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "GRU" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GraphRAG", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "Graph-RAG" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#LLMbasedCLAKGConstruction", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://purl.org/dc/terms/subject" : [ { "@id" : "https://neverblink.eu/ontologies/llm-kg/categories#LLMAugmentedKGConstruction" } ], "http://www.w3.org/2000/01/rdf-schema#comment" : [ { "@value" : "This method uses a Large Language Model (LLM) to automatically extract nodes and relationships from law articles and judgments, integrating them to form the Case-Enhanced Law Article Knowledge Graph (CLAKG). The LLM's role is to reduce manual input and improve the scalability of the KG construction process, directly augmenting the KG construction task." } ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "LLM-based CLAKG Construction" } ], "https://neverblink.eu/ontologies/llm-kg/hasTopCategory" : [ { "@id" : "https://neverblink.eu/ontologies/llm-kg/top-categories#LLMAugmentedKG" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#LightRAG", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "Light-RAG" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#RGCN", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "Relational Graph Convolutional Network" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#TFIDFRAG", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "TFIDF-RAG" } ] } ], "@id" : "https://w3id.org/np/RAjG98Gpzlzwiy3i6yP7Fj1wTHVecNCfQVG0TPWBBT9uc/assertion" }, { "@graph" : [ { "@id" : "https://w3id.org/np/RAjG98Gpzlzwiy3i6yP7Fj1wTHVecNCfQVG0TPWBBT9uc/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.2410.04949" } ] } ], "@id" : "https://w3id.org/np/RAjG98Gpzlzwiy3i6yP7Fj1wTHVecNCfQVG0TPWBBT9uc/provenance" }, { "@graph" : [ { "@id" : "https://w3id.org/np/RAjG98Gpzlzwiy3i6yP7Fj1wTHVecNCfQVG0TPWBBT9uc", "http://purl.org/dc/terms/created" : [ { "@type" : "http://www.w3.org/2001/XMLSchema#dateTime", "@value" : "2026-02-26T15:36:49.991Z" } ], "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://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "LLM-KG assessment for paper 10.48550/arXiv.2410.04949" } ] }, { "@id" : "https://w3id.org/np/RAjG98Gpzlzwiy3i6yP7Fj1wTHVecNCfQVG0TPWBBT9uc/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" : "P93pfc7r1u39hRamkPNlEIzOTgRFo+lCqGSdtIsFdwOp/kTgDmIvGOC+ooYsumdooxYhE66R5a0X+4hdVRjgMxZzJW7e8nRfPlYAJxT7NuaEadVJK/OlDRd0iPz0kEqQclNvbWllnQ++uRQDNWA87H8z0nq9qe3C/h3qiZTS16nBapJh2oJgoLYsK8TIt2r1ATvJlcUv9J/F9mfLai7MUWYZIu2RAXr9cYJ1GKc45hh3/862HHw4xsqg339mirQSucM6QlhOsb3PscjqDU70r5UFGNi+Eg109yfQpODUp1nIfpOu63ltt+IXLpFprc9vnshmLA05qZTumYc+ItMDxg==" } ], "http://purl.org/nanopub/x/hasSignatureTarget" : [ { "@id" : "https://w3id.org/np/RAjG98Gpzlzwiy3i6yP7Fj1wTHVecNCfQVG0TPWBBT9uc" } ], "http://purl.org/nanopub/x/signedBy" : [ { "@id" : "https://neverblink.eu/ontologies/llm-kg/agent" } ] } ], "@id" : "https://w3id.org/np/RAjG98Gpzlzwiy3i6yP7Fj1wTHVecNCfQVG0TPWBBT9uc/pubinfo" } ]