[ { "@graph" : [ { "@id" : "https://w3id.org/np/RAe68J9oUpulv49vQwO43UWKl38DzmSn_K4mIUgBv9k1o", "@type" : [ "http://www.nanopub.org/nschema#Nanopublication" ], "http://www.nanopub.org/nschema#hasAssertion" : [ { "@id" : "https://w3id.org/np/RAe68J9oUpulv49vQwO43UWKl38DzmSn_K4mIUgBv9k1o/assertion" } ], "http://www.nanopub.org/nschema#hasProvenance" : [ { "@id" : "https://w3id.org/np/RAe68J9oUpulv49vQwO43UWKl38DzmSn_K4mIUgBv9k1o/provenance" } ], "http://www.nanopub.org/nschema#hasPublicationInfo" : [ { "@id" : "https://w3id.org/np/RAe68J9oUpulv49vQwO43UWKl38DzmSn_K4mIUgBv9k1o/pubinfo" } ] } ], "@id" : "https://w3id.org/np/RAe68J9oUpulv49vQwO43UWKl38DzmSn_K4mIUgBv9k1o/Head" }, { "@graph" : [ { "@id" : "https://doi.org/10.48550/arXiv.2505.12476", "@type" : [ "http://www.w3.org/ns/prov#Entity" ], "http://purl.org/dc/terms/title" : [ { "@value" : "Enhancing Large Language Models with Reward-guided Tree Search for Knowledge Graph Question and Answering" } ], "http://purl.org/spar/cito/describes" : [ { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#reasoningPathStack" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#rewardGuidedTreeSearchOnGraph" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#selfCriticMonteCarloTreeSearch" } ], "http://purl.org/spar/cito/discusses" : [ { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#deCAF" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#erMPlusNSM" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#fCKBQA" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#flexKBQA" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#gain" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#gnnRAG" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#graftNet" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#interactiveKBQA" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#kbBinder" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#nSM" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#poG" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#pullNet" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#reaRev" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#rnGKBQA" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#roG" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#sRPlusNSM" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#structGPT" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#tiara" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#toG" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#toG20" }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#uniKGQA" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#deCAF", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "DeCAF" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#erMPlusNSM", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "ERM+NSM" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#fCKBQA", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "FC-KBQA" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#flexKBQA", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "FlexKBQA" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#gain", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "GAIN" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#gnnRAG", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "GNN-RAG" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#graftNet", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "GraftNet" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#interactiveKBQA", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "Interactive KBQA" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#kbBinder", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "KB-BINDER" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#nSM", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "NSM" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#poG", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "PoG" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#pullNet", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "PullNet" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#reaRev", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "ReaRev" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#reasoningPathStack", "@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" : "The Reasoning Path Stack is a specific mechanism within RTSoG's Answer Generation stage. It processes the KG-derived weighted reasoning paths in a structured manner, allowing the LLM to effectively utilize this external knowledge during inference to generate more accurate answers." } ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "Reasoning Path Stack" } ], "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#rewardGuidedTreeSearchOnGraph", "@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" : "RTSoG is a training-free framework that enhances LLM performance in KGQA. It uses KGs to retrieve weighted reasoning paths, which are then used by the LLM for answer generation during inference. This directly falls under KGEnhancedLLMInference as KGs are used to provide contextual knowledge to LLMs at inference time." } ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "Reward-guided Tree Search on Graph (RTSoG)" } ], "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#rnGKBQA", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "RnG-KBQA" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#roG", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "RoG" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#sRPlusNSM", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "SR+NSM" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#selfCriticMonteCarloTreeSearch", "@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" : "SC-MCTS is a core component of RTSoG designed to iteratively retrieve weighted reasoning paths from KGs. This method, guided by a reward model (LLM), directly enables the LLM to access and leverage knowledge from KGs during the inference stage for improved KGQA performance." } ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "Self-Critic Monte Carlo Tree Search (SC-MCTS)" } ], "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#structGPT", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "StructGPT" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#tiara", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "TIARA" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#toG", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "ToG" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#toG20", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "ToG2.0" } ] }, { "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#uniKGQA", "@type" : [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label" : [ { "@value" : "UniKGQA" } ] } ], "@id" : "https://w3id.org/np/RAe68J9oUpulv49vQwO43UWKl38DzmSn_K4mIUgBv9k1o/assertion" }, { "@graph" : [ { "@id" : "https://w3id.org/np/RAe68J9oUpulv49vQwO43UWKl38DzmSn_K4mIUgBv9k1o/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.2505.12476" } ] } ], "@id" : "https://w3id.org/np/RAe68J9oUpulv49vQwO43UWKl38DzmSn_K4mIUgBv9k1o/provenance" }, { "@graph" : [ { "@id" : "https://w3id.org/np/RAe68J9oUpulv49vQwO43UWKl38DzmSn_K4mIUgBv9k1o", "http://purl.org/dc/terms/created" : [ { "@type" : "http://www.w3.org/2001/XMLSchema#dateTime", "@value" : "2026-02-26T15:43:29.506Z" } ], "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.2505.12476" } ] }, { "@id" : "https://w3id.org/np/RAe68J9oUpulv49vQwO43UWKl38DzmSn_K4mIUgBv9k1o/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" : "fl34EkbHm3HnLo5L4k0J9J15jZ9lyb84w32PAwRP+TNeXIHmCYfBpCmPZ+lYQla6ys0Dq07vMPJa4kk1UZQnYc5Hc+wOnhDF4tWN5he7YDARtxkoDD4CQNCs/tm0ZoFC8bVyI6KCeO8iLJflOo30pbrLBB00QnDaUimvt7Y78JOP1S1C2/ioAljr/riBwNKgUC+5mzV5H77wJ6tJOnffZmK+7VKqax85YLHec2yTg+elCsO+SjdDrWflrK5f+InKxlvIDwZ9GgFvn64nWoLGmujoFBCC8qUI0qzjw7SbORiJvGT4wy+d2s6FPXgNSwhWWpqSCoGat34UW6wKYnNszw==" } ], "http://purl.org/nanopub/x/hasSignatureTarget" : [ { "@id" : "https://w3id.org/np/RAe68J9oUpulv49vQwO43UWKl38DzmSn_K4mIUgBv9k1o" } ], "http://purl.org/nanopub/x/signedBy" : [ { "@id" : "https://neverblink.eu/ontologies/llm-kg/agent" } ] } ], "@id" : "https://w3id.org/np/RAe68J9oUpulv49vQwO43UWKl38DzmSn_K4mIUgBv9k1o/pubinfo" } ]