https://w3id.org/np/RAVx7L-tHl-XheF8kQ7DFRsxgAXPVzXrgK7z_DxuViXWE/Head https://w3id.org/np/RAVx7L-tHl-XheF8kQ7DFRsxgAXPVzXrgK7z_DxuViXWE http://www.nanopub.org/nschema#hasAssertion https://w3id.org/np/RAVx7L-tHl-XheF8kQ7DFRsxgAXPVzXrgK7z_DxuViXWE/assertion https://w3id.org/np/RAVx7L-tHl-XheF8kQ7DFRsxgAXPVzXrgK7z_DxuViXWE http://www.nanopub.org/nschema#hasProvenance https://w3id.org/np/RAVx7L-tHl-XheF8kQ7DFRsxgAXPVzXrgK7z_DxuViXWE/provenance https://w3id.org/np/RAVx7L-tHl-XheF8kQ7DFRsxgAXPVzXrgK7z_DxuViXWE http://www.nanopub.org/nschema#hasPublicationInfo https://w3id.org/np/RAVx7L-tHl-XheF8kQ7DFRsxgAXPVzXrgK7z_DxuViXWE/pubinfo https://w3id.org/np/RAVx7L-tHl-XheF8kQ7DFRsxgAXPVzXrgK7z_DxuViXWE http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.nanopub.org/nschema#Nanopublication https://w3id.org/np/RAVx7L-tHl-XheF8kQ7DFRsxgAXPVzXrgK7z_DxuViXWE/assertion https://doi.org/10.48550/arXiv.2511.11017 http://purl.org/dc/terms/title AI Agent-Driven Framework for Automated Product Knowledge Graph Construction in E-Commerce https://doi.org/10.48550/arXiv.2511.11017 http://purl.org/spar/cito/describes https://neverblink.eu/ontologies/llm-kg/methods#AiAgentDrivenFramework https://doi.org/10.48550/arXiv.2511.11017 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#BiEtAlCodeKGC https://doi.org/10.48550/arXiv.2511.11017 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#CuiEtAlKGICL https://doi.org/10.48550/arXiv.2511.11017 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#GrapherMethod https://doi.org/10.48550/arXiv.2511.11017 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#KommineniEtAlKGPipeline https://doi.org/10.48550/arXiv.2511.11017 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#LairgiEtAliText2KG https://doi.org/10.48550/arXiv.2511.11017 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#NingEtAlFactualExtraction https://doi.org/10.48550/arXiv.2511.11017 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#XieEtAlPromptKG https://doi.org/10.48550/arXiv.2511.11017 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#XuEtAlProductKGEmbedding https://doi.org/10.48550/arXiv.2511.11017 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#YaoEtAlKGLLM https://doi.org/10.48550/arXiv.2511.11017 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#ZhangEtAlEDCFramework https://doi.org/10.48550/arXiv.2511.11017 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#ZhuEtAlAutoKG https://doi.org/10.48550/arXiv.2511.11017 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/ns/prov#Entity https://neverblink.eu/ontologies/llm-kg/methods#AiAgentDrivenFramework http://purl.org/dc/terms/subject https://neverblink.eu/ontologies/llm-kg/categories#LLMAugmentedKGConstruction https://neverblink.eu/ontologies/llm-kg/methods#AiAgentDrivenFramework http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#AiAgentDrivenFramework http://www.w3.org/2000/01/rdf-schema#comment This framework uses LLM-powered agents to automate the entire process of Knowledge Graph construction. It involves three main stages: ontology creation and expansion (entity/relation discovery), ontology refinement (schema improvement), and knowledge graph population (instance extraction) from unstructured product descriptions, directly addressing KG construction tasks. https://neverblink.eu/ontologies/llm-kg/methods#AiAgentDrivenFramework http://www.w3.org/2000/01/rdf-schema#label AI Agent-Driven Framework https://neverblink.eu/ontologies/llm-kg/methods#AiAgentDrivenFramework https://neverblink.eu/ontologies/llm-kg/hasTopCategory https://neverblink.eu/ontologies/llm-kg/top-categories#LLMAugmentedKG https://neverblink.eu/ontologies/llm-kg/methods#BiEtAlCodeKGC http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#BiEtAlCodeKGC http://www.w3.org/2000/01/rdf-schema#comment Presented by Bi et al., CodeKGC is a method that employs code LLMs and schema-aware prompts for generative KG tasks, enhanced by rationale-based generation. https://neverblink.eu/ontologies/llm-kg/methods#BiEtAlCodeKGC http://www.w3.org/2000/01/rdf-schema#label CodeKGC https://neverblink.eu/ontologies/llm-kg/methods#CuiEtAlKGICL http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#CuiEtAlKGICL http://www.w3.org/2000/01/rdf-schema#comment Proposed by Cui et al., KG-ICL is a method that combines in-context learning with a prompt graph and unified tokenization to achieve strong generalization across various KG tasks. https://neverblink.eu/ontologies/llm-kg/methods#CuiEtAlKGICL http://www.w3.org/2000/01/rdf-schema#label KG-ICL https://neverblink.eu/ontologies/llm-kg/methods#GrapherMethod http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#GrapherMethod http://www.w3.org/2000/01/rdf-schema#comment Grapher is discussed as a method that generates end-to-end KGs by dividing tasks into entity and relation extraction using pre-trained Language Models. https://neverblink.eu/ontologies/llm-kg/methods#GrapherMethod http://www.w3.org/2000/01/rdf-schema#label Grapher https://neverblink.eu/ontologies/llm-kg/methods#KommineniEtAlKGPipeline http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#KommineniEtAlKGPipeline http://www.w3.org/2000/01/rdf-schema#comment This method is mentioned as a prior LLM-based pipeline that aims to minimize human intervention in KG construction by incorporating competency-question-based ontology generation and LLM-driven evaluation. https://neverblink.eu/ontologies/llm-kg/methods#KommineniEtAlKGPipeline http://www.w3.org/2000/01/rdf-schema#label Kommineni et al.'s Pipeline https://neverblink.eu/ontologies/llm-kg/methods#LairgiEtAliText2KG http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#LairgiEtAliText2KG http://www.w3.org/2000/01/rdf-schema#comment Proposed by Lairgi et al., this method is presented as a zero-shot, plug-and-play system for distilling unstructured input into KGs with minimal post-processing. https://neverblink.eu/ontologies/llm-kg/methods#LairgiEtAliText2KG http://www.w3.org/2000/01/rdf-schema#label iText2KG https://neverblink.eu/ontologies/llm-kg/methods#NingEtAlFactualExtraction http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#NingEtAlFactualExtraction http://www.w3.org/2000/01/rdf-schema#comment This method by Ning et al. explores factual knowledge extraction for KGs via prompt templates and parameter tuning to improve accuracy. https://neverblink.eu/ontologies/llm-kg/methods#NingEtAlFactualExtraction http://www.w3.org/2000/01/rdf-schema#label Ning et al.'s Factual Knowledge Extraction https://neverblink.eu/ontologies/llm-kg/methods#XieEtAlPromptKG http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#XieEtAlPromptKG http://www.w3.org/2000/01/rdf-schema#comment Xie et al. introduced PromptKG, a toolkit designed to integrate prompt-learning methods for various Knowledge Graph applications. https://neverblink.eu/ontologies/llm-kg/methods#XieEtAlPromptKG http://www.w3.org/2000/01/rdf-schema#label PromptKG https://neverblink.eu/ontologies/llm-kg/methods#XuEtAlProductKGEmbedding http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#XuEtAlProductKGEmbedding http://www.w3.org/2000/01/rdf-schema#comment This embedding method, proposed by Xu et al., is tailored for product KGs and uses multimodal data to enhance KG completion and recommendation tasks. https://neverblink.eu/ontologies/llm-kg/methods#XuEtAlProductKGEmbedding http://www.w3.org/2000/01/rdf-schema#label Xu et al.'s Embedding Method https://neverblink.eu/ontologies/llm-kg/methods#YaoEtAlKGLLM http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#YaoEtAlKGLLM http://www.w3.org/2000/01/rdf-schema#comment This method, presented by Yao et al., utilizes entity/relation prompts for triple classification and relation prediction, focusing on Knowledge Graph completion tasks. https://neverblink.eu/ontologies/llm-kg/methods#YaoEtAlKGLLM http://www.w3.org/2000/01/rdf-schema#label KG-LLM https://neverblink.eu/ontologies/llm-kg/methods#ZhangEtAlEDCFramework http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#ZhangEtAlEDCFramework http://www.w3.org/2000/01/rdf-schema#comment This method, proposed by Zhang et al., is discussed as a prior LLM-based approach for automated KG construction, which separates open information extraction, schema creation, and canonicalization. https://neverblink.eu/ontologies/llm-kg/methods#ZhangEtAlEDCFramework http://www.w3.org/2000/01/rdf-schema#label EDC Framework https://neverblink.eu/ontologies/llm-kg/methods#ZhuEtAlAutoKG http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#ZhuEtAlAutoKG http://www.w3.org/2000/01/rdf-schema#comment This framework, introduced by Zhu et al., is discussed as a multi-agent system that combines LLMs with external data for KG construction. https://neverblink.eu/ontologies/llm-kg/methods#ZhuEtAlAutoKG http://www.w3.org/2000/01/rdf-schema#label AutoKG Framework https://w3id.org/np/RAVx7L-tHl-XheF8kQ7DFRsxgAXPVzXrgK7z_DxuViXWE/provenance https://w3id.org/np/RAVx7L-tHl-XheF8kQ7DFRsxgAXPVzXrgK7z_DxuViXWE/assertion http://www.w3.org/ns/prov#wasAttributedTo https://neverblink.eu/ontologies/llm-kg/agent 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