{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T07:02:33Z","timestamp":1767942153117,"version":"3.49.0"},"reference-count":28,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T00:00:00Z","timestamp":1767744000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["24K15078"],"award-info":[{"award-number":["24K15078"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Procedural knowledge is essential in specialized domains, and natural language tools for retrieving procedural knowledge are necessary for non-expert users to facilitate their understanding and learning. In this study, we focus on function decomposition trees, a framework for representing procedural knowledge, and propose a natural language interface leveraging Retrieval-Augmented Generation (RAG). The natural language interface converts the user\u2019s inputs into SPARQL queries, retrieving relevant data and subsequently presenting them in an accessible and chat-based format. Such a flexible and purpose-driven search facilitates users\u2019 understanding of functions of artifacts or human actions and their performance of these actions. We demonstrate that the tool effectively retrieves actions, goals, and dependencies using an illustrative real-world example of a function decomposition tree. In addition, we evaluated the system by comparing it with ChatGPT 4o and Microsoft GraphRAG. The results suggest that the system can deliver responses that are both necessary and sufficient for users\u2019 needs, while the outputs of other systems lack the key elements and return redundant information.<\/jats:p>","DOI":"10.3390\/info17010055","type":"journal-article","created":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T11:46:43Z","timestamp":1767786403000},"page":"55","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["RAG-Based Natural Language Interface for Goal-Oriented Knowledge Graphs and Its Evaluation"],"prefix":"10.3390","volume":"17","author":[{"given":"Kosuke","family":"Yano","sequence":"first","affiliation":[{"name":"Graduate School of Information Science and Engineering, Ritsumeikan University, Osaka 567-8570, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yoshinobu","family":"Kitamura","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Ritsumeikan University, Osaka 567-8570, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3493-1076","authenticated-orcid":false,"given":"Kazuhiro","family":"Kuwabara","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Ritsumeikan University, Osaka 567-8570, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"100850","DOI":"10.1016\/j.websem.2024.100850","article-title":"Procedural knowledge management in Industry 5.0: Challenges and opportunities for knowledge graphs","volume":"84","author":"Celino","year":"2024","journal-title":"J. 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