{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T19:12:19Z","timestamp":1772910739568,"version":"3.50.1"},"publisher-location":"Cham","reference-count":50,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032131089","type":"print"},{"value":"9783032131096","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T00:00:00Z","timestamp":1766448000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T00:00:00Z","timestamp":1766448000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-13109-6_15","type":"book-chapter","created":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T07:27:37Z","timestamp":1766388457000},"page":"208-223","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Knowledge Conceptualization Impacts RAG Efficacy"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2287-1198","authenticated-orcid":false,"given":"Chris Davis","family":"Jaldi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1735-2377","authenticated-orcid":false,"given":"Anmol","family":"Saini","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-1201-2029","authenticated-orcid":false,"given":"Elham","family":"Ghiasi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"O.","family":"Divine Eziolise","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4283-8701","authenticated-orcid":false,"given":"Cogan","family":"Shimizu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,12,23]]},"reference":[{"key":"15_CR1","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1016\/S1574-6526(07)03003-9","volume":"3","author":"F Baader","year":"2008","unstructured":"Baader, F., Horrocks, I., Sattler, U.: Description logics. Found. Artif. Intell. 3, 135\u2013179 (2008)","journal-title":"Found. Artif. Intell."},{"key":"15_CR2","doi-asserted-by":"crossref","unstructured":"Banerjee, S., Agarwal, A., Singla, S.: LLMs Will Always Hallucinate, and We Need to Live With This. arXiv preprint arXiv:2409.05746 (2024)","DOI":"10.1007\/978-3-031-99965-9_39"},{"key":"15_CR3","unstructured":"Bellemare-Pepin, A., Lespinasse, F., Th\u00f6lke, P., Harel, Y., Mathewson, K., Olson, J.A., Bengio, Y., Jerbi, K.: Divergent Creativity in Humans and Large Language Models. arXiv preprint arXiv:2405.13012 (2024)"},{"key":"15_CR4","doi-asserted-by":"crossref","unstructured":"Bezerra, C., Freitas, F., Santana, F.: Evaluating ontologies with competency questions. In: 2013 IEEE\/WIC\/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technologies, vol. 3, pp. 284\u2013285. IEEE (2013)","DOI":"10.1109\/WI-IAT.2013.199"},{"key":"15_CR5","unstructured":"For Biomedical Informatics\u00a0Research, S.C.: Prot\u00e9g\u00e9 Ontology Editor and Framework. https:\/\/protege.stanford.edu\/ (2025). Accessed 11 May 2025"},{"key":"15_CR6","unstructured":"Boylan, J., Mangla, S., Thorn, D., Ghalandari, D.G., Ghaffari, P., Hokamp, C.: Kgvalidator: A Framework for Automatic Validation of Knowledge Graph Construction. arXiv preprint arXiv:2404.15923 (2024)"},{"key":"15_CR7","unstructured":"Christou, A., Dave, B., Shimizu, C.: Experiments in graph structure and knowledge graph embeddings. Neurosymbolic Artif. Intell. (2024)"},{"key":"15_CR8","doi-asserted-by":"crossref","unstructured":"Dave, B., Christou, A., Shimizu, C.: Towards understanding the impact of graph structure on knowledge graph embeddings. In: International Conference on Neural-Symbolic Learning and Reasoning, pp. 41\u201350. Springer (2024)","DOI":"10.1007\/978-3-031-71170-1_5"},{"key":"15_CR9","unstructured":"Emonet, V., Bolleman, J., Duvaud, S., de\u00a0Farias, T.M., Sima, A.C.: LLM-Based Sparql Query Generation from Natural Language Over Federated Knowledge Graphs. arXiv preprint arXiv:2410.06062 (2024)"},{"key":"15_CR10","unstructured":"Enslaved: Peoples of the Historical Slave Trade. https:\/\/enslaved.org\/"},{"key":"15_CR11","unstructured":"Enslaved.org cqs. https:\/\/docs.enslaved.org\/competencyQuestions\/"},{"key":"15_CR12","unstructured":"Gehrke, B., Mossakowski, T.: Extending owl2 manchester syntax to include missing features from owl2 abstract syntax. In: Description Logics (2023)"},{"key":"15_CR13","unstructured":"Gemini Flash 2.0. https:\/\/cloud.google.com\/vertex-ai\/generative-ai\/docs\/models\/gemini\/2-0-flash. Accessed 11 May 2025"},{"issue":"2","key":"15_CR14","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1006\/knac.1993.1008","volume":"5","author":"TR Gruber","year":"1993","unstructured":"Gruber, T.R.: A translation approach to portable ontology specifications. Knowl. Acquis. 5(2), 199\u2013220 (1993)","journal-title":"Knowl. Acquis."},{"issue":"2","key":"15_CR15","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1145\/3397512","volume":"64","author":"P Hitzler","year":"2021","unstructured":"Hitzler, P.: A review of the semantic web field. Commun. ACM 64(2), 76\u201383 (2021)","journal-title":"Commun. ACM"},{"key":"15_CR16","doi-asserted-by":"crossref","unstructured":"Hitzler, P., Sarker, M.K.: Neuro-Symbolic Artificial Intelligence: The State of the Art (2022)","DOI":"10.3233\/FAIA342"},{"key":"15_CR17","unstructured":"Horridge, M., Drummond, N., Goodwin, J., Rector, A.L., Stevens, R., Wang, H.: The manchester owl syntax. In: OWLed, vol. 216 (2006)"},{"key":"15_CR18","unstructured":"Horridge, M., Patel-Schneider, P.F.: Owl 2 Web Ontology Language: Manchester Syntax, 2nd edn. w3C Working Group Note. https:\/\/www.w3.org\/TR\/owl2-manchester-syntax\/ (2012). Accessed 11 May 2025"},{"key":"15_CR19","doi-asserted-by":"crossref","unstructured":"Huang, J., Chang, K.C.C.: Towards Reasoning in Large Language Models: A Survey. arXiv preprint arXiv:2212.10403 (2022)","DOI":"10.18653\/v1\/2023.findings-acl.67"},{"key":"15_CR20","unstructured":"Knowledge-Conceptualization-GraphRAG. https:\/\/github.com\/kastle-lab\/knowledge-conceptualization-graphrag. Accessed 30 July 2025"},{"key":"15_CR21","unstructured":"KnowWhereGraph. https:\/\/knowwheregraph.org\/"},{"key":"15_CR22","unstructured":"Kovriguina, L., Teucher, R., Radyush, D., Mouromtsev, D.: SPARQLGEN: one-shot prompt-based approach for SPARQL query generation. In: SEMANTiCS (Posters & Demos) (2023)"},{"key":"15_CR23","first-page":"9459","volume":"33","author":"P Lewis","year":"2020","unstructured":"Lewis, P., Perez, E., Piktus, A., Petroni, F., et al.: Retrieval-augmented generation for knowledge-intensive NLP tasks. Adv. Neural Inf. Process. Syst. 33, 9459\u20139474 (2020)","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"15_CR24","unstructured":"OntoLex: TLexicon Model for Ontologies\u2014Community Report. https:\/\/www.w3.org\/2016\/05\/ontolex\/. Accessed 11 May 2025"},{"issue":"3","key":"15_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3186727","volume":"51","author":"Y Liu","year":"2018","unstructured":"Liu, Y., Safavi, T., Dighe, A., Koutra, D.: Graph summarization methods and applications: a survey. ACM Comput. Surv. (CSUR) 51(3), 1\u201334 (2018)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"15_CR26","doi-asserted-by":"crossref","unstructured":"Lu, A., Zhang, H., Zhang, Y., Wang, X., Yang, D.: Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints. arXiv preprint arXiv:2302.09185 (2023)","DOI":"10.18653\/v1\/2023.findings-eacl.148"},{"key":"15_CR27","first-page":"46534","volume":"36","author":"A Madaan","year":"2023","unstructured":"Madaan, A., Tandon, N., Gupta, P., Hallinan, S., et al.: Self-refine: iterative refinement with self-feedback. Adv. Neural Inf. Process. Syst. 36, 46534\u201346594 (2023)","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"9","key":"15_CR28","doi-asserted-by":"publisher","first-page":"115","DOI":"10.3390\/bdcc8090115","volume":"8","author":"A Mansurova","year":"2024","unstructured":"Mansurova, A., Mansurova, A., Nugumanova, A.: QA-RAG: Exploring LLM reliance on external knowledge. Big Data Cogn. Comput. 8(9), 115 (2024)","journal-title":"Big Data Cogn. Comput."},{"key":"15_CR29","unstructured":"Meyer, L.P., Frey, J., Brei, F., Arndt, N.: Assessing SPARQL Capabilities of Large Language Models. arXiv preprint arXiv:2409.05925 (2024)"},{"key":"15_CR30","unstructured":"Mistral Large. https:\/\/mistral.ai\/news\/mistral-large-2407"},{"key":"15_CR31","doi-asserted-by":"crossref","unstructured":"Norouzi, S.S., Barua, A., Christou, A., Gautam, N., Eells, A., Hitzler, P., Shimizu, C.: Ontology population using LLMs. In: Handbook on Neurosymbolic AI and Knowledge Graphs, pp. 421\u2013438. IOS Press (2025)","DOI":"10.3233\/FAIA250217"},{"key":"15_CR32","unstructured":"ChatGPT. https:\/\/openai.com\/index\/hello-gpt-4o\/. Accessed 11 May 2025"},{"key":"15_CR33","unstructured":"Ozsoy, M.G., Messallem, L., Besga, J., Minneci, G.: Text2cypher: Bridging Natural Language and Graph Databases. arXiv preprint arXiv:2412.10064 (2024)"},{"issue":"4","key":"15_CR34","doi-asserted-by":"publisher","first-page":"1019","DOI":"10.1177\/01655515221112844","volume":"50","author":"E Rajabi","year":"2024","unstructured":"Rajabi, E., Etminani, K.: Knowledge-graph-based explainable AI: a systematic review. J. Inf. Sci. 50(4), 1019\u20131029 (2024)","journal-title":"J. Inf. Sci."},{"key":"15_CR35","doi-asserted-by":"crossref","unstructured":"Sequeda, J., Allemang, D., Jacob, B.: A benchmark to understand the role of knowledge graphs on large language model\u2019s accuracy for question answering on enterprise SQL databases. In: Proceedings of the 7th Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA), pp. 1\u201312 (2024)","DOI":"10.1145\/3661304.3661901"},{"key":"15_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.websem.2024.100823","volume":"82","author":"C Shimizu","year":"2024","unstructured":"Shimizu, C., Eells, A., Gonzalez, S., Zhou, L., Hitzler, P., Sheill, A., Foley, C., Rehberger, D.: Ontology design facilitating Wikibase integration\u2014and a worked example for historical data. J. Web Semant. 82, 100823 (2024)","journal-title":"J. Web Semant."},{"key":"15_CR37","doi-asserted-by":"crossref","unstructured":"Shimizu, C., Hitzler, P.: Accelerating knowledge graph and ontology engineering with large language models. J. Web Semant. 100862 (2025)","DOI":"10.1016\/j.websem.2025.100862"},{"key":"15_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.websem.2020.100567","volume":"63","author":"C Shimizu","year":"2020","unstructured":"Shimizu, C., Hitzler, P., Hirt, Q., Rehberger, D., Estrecha, S.G., Foley, C., Sheill, A.M., Hawthorne, W., Mixter, J., Watrall, E., et al.: The enslaved ontology: peoples of the historic slave trade. J. Web Semant. 63, 100567 (2020)","journal-title":"J. Web Semant."},{"key":"15_CR39","doi-asserted-by":"crossref","unstructured":"Shimizu, C., Stephen, S., Christou, A., Currier, K., Mahdavinejad, M.S., Norouzi, S.S., Dalal, A., Barua, A., Fisher, C.K., D\u2019Onofrio, A., et\u00a0al.: Knowwheregraph-lite: a perspective of the knowwheregraph. In: Iberoamerican Knowledge Graphs and Semantic Web Conference, pp. 199\u2013212. Springer (2023)","DOI":"10.1007\/978-3-031-47745-4_15"},{"key":"15_CR40","unstructured":"Simonds, T., Yoshiyama, A.: Ladder: Self-Improving LLMs Through Recursive Problem Decomposition. arXiv preprint arXiv:2503.00735 (2025)"},{"key":"15_CR41","doi-asserted-by":"crossref","unstructured":"Soman, K., Rose, P.W., Morris, J.H., Akbas, R.E., Smith, B., Peetoom, B., Villouta-Reyes, C., Cerono, G., Shi, Y., Rizk-Jackson, A., et\u00a0al.: Biomedical knowledge graph-optimized prompt generation for large language models. Bioinformatics 40(9), btae560 (2024)","DOI":"10.1093\/bioinformatics\/btae560"},{"key":"15_CR42","doi-asserted-by":"crossref","unstructured":"Song, Z., Yan, B., Liu, Y., Fang, M., Li, M., Yan, R., Chen, X.: Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey. https:\/\/arxiv.org\/abs\/2502.10708 (2025)","DOI":"10.18653\/v1\/2025.findings-emnlp.1379"},{"key":"15_CR43","doi-asserted-by":"crossref","unstructured":"Tam, Z.R., Wu, C.K., Tsai, Y.L., Lin, C.Y., Lee, H.Y., Chen, Y.N.: Let Me Speak Freely? A Study on the Impact of Format Restrictions on Performance of Large Language Models. arXiv preprint arXiv:2408.02442 (2024)","DOI":"10.18653\/v1\/2024.emnlp-industry.91"},{"key":"15_CR44","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., Polosukhin, I.: Attention is all you need. Adv. Neural Inf. Process. Syst. 30 (2017)"},{"key":"15_CR45","unstructured":"Wang, Y., Zhao, Y.: Metacognitive Prompting Improves Understanding in Large Language Models. arXiv preprint arXiv:2308.05342 (2023)"},{"key":"15_CR46","doi-asserted-by":"crossref","unstructured":"Yang, S., Teng, M., Dong, X., Bo, F.: LLM-based SPARQL generation with selected schema from large scale knowledge base. In: China Conference on Knowledge Graph and Semantic Computing, pp. 304\u2013316. Springer (2023)","DOI":"10.1007\/978-981-99-7224-1_24"},{"key":"15_CR47","doi-asserted-by":"crossref","unstructured":"Zahera, H.M., Ali, M., Sherif, M.A., et\u00a0al.: Generating SPARQL from natural language using chain-of-thoughts prompting. In: Proceedings of the 20th International Conference on Semantic Systems, vol.\u00a060, pp. 353\u2013368 (2024)","DOI":"10.3233\/SSW240028"},{"key":"15_CR48","unstructured":"Zhang, Q., Chen, S., Bei, Y., Yuan, Z., Zhou, H., Hong, Z., Dong, J., Chen, H., Chang, Y., Huang, X.: A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models. arXiv preprint arXiv:2501.13958 (2025)"},{"key":"15_CR49","unstructured":"Zhao, S., Yang, Y., Wang, Z., He, Z., Qiu, L.K., Qiu, L.: Retrieval Augmented Generation (rag) and Beyond: A Comprehensive Survey on How to Make your LLMs Use External Data More Wisely. arXiv preprint arXiv:2409.14924 (2024)"},{"key":"15_CR50","unstructured":"Zhu, R., Shimizu, C., Stephen, S., Fisher, C.K., Thelen, T., Currier, K., Janowicz, K., Hitzler, P., Schildhauer, M., Li, W., et\u00a0al.: The Knowwheregraph: A Large-Scale Geo-knowledge Graph for Interdisciplinary Knowledge Discovery and Geo-enrichment. arXiv preprint arXiv:2502.13874 (2025)"}],"container-title":["Lecture Notes in Computer Science","Knowledge Graphs and Semantic Web"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-13109-6_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T07:27:45Z","timestamp":1766388465000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-13109-6_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,23]]},"ISBN":["9783032131089","9783032131096"],"references-count":50,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-13109-6_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,23]]},"assertion":[{"value":"23 December 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"KGSWC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Knowledge Graph and Semantic Web Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Leipzig","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 November 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 November 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"kgswc2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/kgsw.org\/index.php","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}