KG-First, LLM-Fallback: A Hybrid Microservice for Grounded Skill Search and Explanation
Authoritative competency frameworks such as ESCO, ROME, and O*NET are essential for aligning education with labor market needs, yet their technical complexity and structural heterogeneity hinder practical adoption by educators. This paper introduces SkillGraph-Service, an interoperable microservice designed to bridge this gap by unifying these resources into a provenance-preserving Knowledge Graph (KG). Adopting a KG-first, LLM-fallback architecture, the system combines symbolic rigor with sub-s
Record details
Published: 2 May 2026
Source: arXiv
Category: Research
Topics: Jobs & economy · Children & education
Retrieved: 14 July 2026
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How to cite this record
ethics.ai (2 May 2026), “KG-First, LLM-Fallback: A Hybrid Microservice for Grounded Skill Search and Explanation,” evidence record 5069, https://ethics.ai/record/5069 (originally published by arXiv).
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