cs.CLFeb 28, 2026

SSKG Hub: An Expert-Guided Platform for LLM-Empowered Sustainability Standards Knowledge Graphs

Authors: Chaoyue He, Xin Zhou, Xinjia Yu, Lei Zhang, Yan Zhang, Yi Wu, Lei Xiao, Liangyue Li, 

Organizations: Alibaba-NTU Global e-Sustainability CorpLab (ANGEL), Singapore · Alibaba Group, China

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Abstract

Sustainability disclosure standards (e.g., GRI, SASB, TCFD, IFRS S2) are comprehensive yet lengthy, terminology-dense, and highly cross-referential, hindering structured analysis and downstream use. We present SSKG Hub (Sustainability Standards Knowledge Graph Hub), a research prototype and interactive web platform that transforms standards into auditable knowledge graphs (KGs) through an LLM-centered, expert-guided pipeline. The system integrates automatic standard identification, configurable chunking, standard-specific prompting, robust triple parsing, and provenance-aware Neo4j storage with fine-grained audit metadata. LLM extraction produces a provenance-linked Draft KG, which is reviewed, curated, and formally promoted to a Certified KG through meta-expert adjudication. A role-based governance framework covering read-only guest access, expert review and CRUD operations, meta-expert certification, and administrative oversight ensures traceability and accountability across draft and certified states. Beyond graph exploration and triple-level evidence tracing, SSKG Hub supports cross-KG fusion, KG-driven tasks, and dedicated modules for insights and curated resources. We validate the platform through a comprehensive expert-led KG review case study that demonstrates end-to-end curation and quality assurance. The web application is publicly available at www.sskg-hub.com.

Figures & tables

Figure 1: System overview of SSKG Hub. Sustainability standards PDFs (e.g., GRI, SASB, IFRS S2, TCFD) are processed via text extraction (PyMuPDF), LLM-based identification and chunking, and standard-specific prompting. Qwen-Max extracts normalized (subject, predicate, object) triples with aligned provenance, forming a provenance-aware Draft KG stored in Neo4j with audit metadata. Through expert review and meta-expert certification, validated triples are promoted to a Certified KG . On top of this graph core, SSKG Hub supports catalog management, interactive graph exploration with evidence tracing, triple inspection, cross-KGs fusion, downstream tasks (e.g., KGQA, reasoning paths), analytics, and immutable audit logging under role-based governance.
Figure 2: SSKG Hub UI highlights. Left: (1) standard-specific extraction setup, where users upload a sustainability standards PDF, verify the detected standard family, and inspect tailored prompt templates; (2) real-time ingestion monitoring with chunk-level progress and model transparency; and (3) a structured ingestion summary reporting document metadata and graph statistics. Right: (1) provenance-backed verification that links each triple to its source page and evidence span, with editable CRUD operations on selected (subject, predicate, object) triples; (2) an overall graph overview with zoom controls; (3) an interactive KG canvas for navigation, filtering, and structural exploration; and (4) a side panel displaying the original PDF with search and export utilities for traceable validation.
CategoryRepresentative capabilities
Standards KGQAQA over a selected SSKG: entity matching, concise answers, reasoning paths, subgraph view.
Reasoning & path analysisBounded-hop reasoning and source–target path search with stepwise paths and mini-graph view.
Comparative & anomaly analysisMulti-entity comparison (fact counts, shared/unique predicates) and prompt-based anomaly detection.
Subgraph & structure explorationQuery-driven subgraphs, entity profiles, impact analysis, predicate-focused exploration.
Quality & curation checksSchema diagnostics, coverage-gap heuristics, duplicate/alias detection.
Provenance tracingEvidence retrieval via filters with source-linked triples for verification.
Table 1: Overview of Downstream Tasks.
Appendix figures & tables1 asset

Supplementary material from the paper’s appendix.

Appendix

SystemIn →\rightarrow KGProv.Gov. Tasks
PDF/RAG×\times /partpart×\times limited
Protégé/ WebProtégé/ VocBenchmanual–collab –
OntoMetric✓\checkmark✓\checkmarkvalidate not unified demo
SSKG Hub✓\checkmark✓\checkmarkexpert+meta KGQA, fusion
Appendix
Table 2: SSKG Hub uniquely combines certification, auditability, and KG tasks in one platform.
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