GROUNDEDKG-RAG: Grounded Knowledge Graph Index for Long-document Question Answering explores GroundedKG-RAG: A RAG system that explicitly extracts and grounds knowledge graphs from source documents for efficient and factually accurate long-document question answering.. Commercial viability score: 7/10 in RAG Systems.
Use This Via API or MCP
This route is the stable paper-level surface for citations, viability, references, and downstream handoffs. Use it as the proof layer behind Signal Canvas, workspace creation, and launch-pack generation.
Freshness
Canonical route: /paper/groundedkg-rag-grounded-knowledge-graph-index-for-long-document-question-answering
Proof data is outside the preferred freshness window.
Proof Quality
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Agent Handoff
Canonical ID groundedkg-rag-grounded-knowledge-graph-index-for-long-document-question-answering | Route /paper/groundedkg-rag-grounded-knowledge-graph-index-for-long-document-question-answering
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/groundedkg-rag-grounded-knowledge-graph-index-for-long-document-question-answeringMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.04359"
}
}source_context
{
"surface": "paper",
"mode": "paper",
"query": "GROUNDEDKG-RAG: Grounded Knowledge Graph Index for Long-document Question Answering",
"normalized_query": "2604.04359",
"route": "/paper/groundedkg-rag-grounded-knowledge-graph-index-for-long-document-question-answering",
"paper_ref": "groundedkg-rag-grounded-knowledge-graph-index-for-long-document-question-answering",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Constellation, claims, and market context stay visible on the paper proof page even when commercialization rails are held back for incomplete proof receipts.
Preparing verified analysis
Dimensions overall score 7.0
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