[ { "@id": "https://w3id.org/np/RAkEC3g1S3-AUa4oS1tpjvWWtUUz8VEbzlSRYczzMRW3A/Head", "@graph": [ { "@id": "https://w3id.org/np/RAkEC3g1S3-AUa4oS1tpjvWWtUUz8VEbzlSRYczzMRW3A", "http://www.nanopub.org/nschema#hasAssertion": [ { "@id": "https://w3id.org/np/RAkEC3g1S3-AUa4oS1tpjvWWtUUz8VEbzlSRYczzMRW3A/assertion" } ], "http://www.nanopub.org/nschema#hasProvenance": [ { "@id": "https://w3id.org/np/RAkEC3g1S3-AUa4oS1tpjvWWtUUz8VEbzlSRYczzMRW3A/provenance" } ], "http://www.nanopub.org/nschema#hasPublicationInfo": [ { "@id": "https://w3id.org/np/RAkEC3g1S3-AUa4oS1tpjvWWtUUz8VEbzlSRYczzMRW3A/pubinfo" } ], "@type": [ "http://www.nanopub.org/nschema#Nanopublication" ] } ] }, { "@id": "https://w3id.org/np/RAkEC3g1S3-AUa4oS1tpjvWWtUUz8VEbzlSRYczzMRW3A/assertion", "@graph": [ { "@id": "https://doi.org/10.48550/arXiv.2502.03992", "http://purl.org/dc/terms/title": [ { "@value": "Ontology-Guided, Hybrid Prompt Learning for Generalization in Knowledge Graph Question Answering" } ], "http://purl.org/spar/cito/describes": [ { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#OntoSCPrompt" } ], "http://purl.org/spar/cito/discusses": [ { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#EmbedKGQA" }, { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#GraphNet" }, { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#HGNet" }, { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#PullNet" }, { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#STaGQA" }, { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#TERP" } ], "@type": [ "http://www.w3.org/ns/prov#Entity" ] }, { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#OntoSCPrompt", "http://purl.org/dc/terms/subject": [ { "@id": "https://neverblink.eu/ontologies/llm-kg/categories#LLMAugmentedKGQuestionAnswering" } ], "@type": [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#comment": [ { "@value": "This method introduces a novel two-stage LLM-based KGQA system to generalize across heterogeneous KGs. It utilizes an ontology-guided hybrid prompt learning strategy, integrating KG ontology into prompts for semantic parsing and KG content population, and employs task-specific decoding strategies to ensure SPARQL query validity. The primary goal is to improve KGQA performance and generalization using LLMs." } ], "http://www.w3.org/2000/01/rdf-schema#label": [ { "@value": "OntoSCPrompt" } ], "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#EmbedKGQA", "@type": [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label": [ { "@value": "EmbedKGQA" } ] }, { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#GraphNet", "@type": [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label": [ { "@value": "GraphNet" } ] }, { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#HGNet", "@type": [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label": [ { "@value": "HGNet" } ] }, { "@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#STaGQA", "@type": [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label": [ { "@value": "STaG-QA" } ] }, { "@id": "https://neverblink.eu/ontologies/llm-kg/methods#TERP", "@type": [ "http://purl.org/spar/fabio/Workflow" ], "http://www.w3.org/2000/01/rdf-schema#label": [ { "@value": "TERP" } ] } ] }, { "@id": "https://w3id.org/np/RAkEC3g1S3-AUa4oS1tpjvWWtUUz8VEbzlSRYczzMRW3A/provenance", "@graph": [ { "@id": "https://w3id.org/np/RAkEC3g1S3-AUa4oS1tpjvWWtUUz8VEbzlSRYczzMRW3A/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.2502.03992" } ] } ] }, { "@id": "https://w3id.org/np/RAkEC3g1S3-AUa4oS1tpjvWWtUUz8VEbzlSRYczzMRW3A/pubinfo", "@graph": [ { "@id": "https://w3id.org/np/RAkEC3g1S3-AUa4oS1tpjvWWtUUz8VEbzlSRYczzMRW3A", "http://purl.org/dc/terms/created": [ { "@value": "2026-02-26T16:27:05.185Z", "@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://www.w3.org/2000/01/rdf-schema#label": [ { "@value": "LLM-KG assessment for paper 10.48550/arXiv.2502.03992" } ] }, { "@id": "https://w3id.org/np/RAkEC3g1S3-AUa4oS1tpjvWWtUUz8VEbzlSRYczzMRW3A/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": "WZClPit8AH5yMSgPM+5G/nXlJD05q3evyfe95joXw2MLY0iyuUBoyFK71Jz0MHQP/Ob0QYvqWzqkkFFzvzUk/k/8/Ca957QufHRByXVJUrYthOuvFGeu2uwgQUclUqDdypX0XDciO1BjAMjG5lXchxjGNOk8IXsk2uEvhp+N/6L3aUM0FU+46QUiMZ9DxxisH8suMexG5rvCbI++ntu9+AokkK3dFhu6u2q1GPPZzTdYiEhHrfXzEmqVxOtHcPjnEeMVZwUv5T8gFYQ9POYRQEdzK8tj/orSOyBB++XHRj/FkdtT+Zny0Xqgo0l3cQuvDv7H0AaN6ZWSu7qZo5tmhg==" } ], "http://purl.org/nanopub/x/hasSignatureTarget": [ { "@id": "https://w3id.org/np/RAkEC3g1S3-AUa4oS1tpjvWWtUUz8VEbzlSRYczzMRW3A" } ], "http://purl.org/nanopub/x/signedBy": [ { "@id": "https://neverblink.eu/ontologies/llm-kg/agent" } ] } ] } ]