{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T18:32:31Z","timestamp":1769452351116,"version":"3.49.0"},"reference-count":48,"publisher":"PeerJ","license":[{"start":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T00:00:00Z","timestamp":1769385600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["42261055"],"award-info":[{"award-number":["42261055"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Guangxi Science and Technology Major Special Project","award":["Guike AA23062039-1"],"award-info":[{"award-number":["Guike AA23062039-1"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>Generative artificial intelligence (GAI) is gaining increasing popularity, but its applications in the Geographical Information System (GIS) domain remain limited. Consequently, answers to domain-specific questions often lack depth and specialization. GraphRAG presents a promising solution by building a knowledge graph, integrating contextual information from a knowledge base, and generating higher-quality answers. In this study, we use GraphRAG to enhance a pretrained large language model (LLM) through a retrieval-augmented generation framework, presenting a domain-specific chatbot named G-Pro Bot. Our evaluation, which includes both automated and manual evaluation, confirms the strong performance of G-Pro Bot in comprehending GIS knowledge and generating accurate, context-aware responses compared with baseline models. This makes the G-Pro Bot well suited for use in GIS education and decision-support scenarios. To the best of our knowledge, this research represents one of the earliest applications of GraphRAG in the development of a GIS chatbot, and it validates a lightweight, resource-accessible strategy for building high-performing, domain-specific artificial intelligence (AI) systems. The findings provide a valuable blueprint for creating reliable and easily deployable question-answering systems in other professional fields.<\/jats:p>","DOI":"10.7717\/peerj-cs.3520","type":"journal-article","created":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T08:30:23Z","timestamp":1769416223000},"page":"e3520","source":"Crossref","is-referenced-by-count":0,"title":["G-Pro bot: a GraphRAG-powered GIS (Geographical information system) chatbot"],"prefix":"10.7717","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-7302-693X","authenticated-orcid":true,"given":"Xiaohuan","family":"Wang","sequence":"first","affiliation":[{"name":"Institute of International Rivers and Eco-Security, Yunnan University, Kunming, Yunnan, China"},{"name":"State Key Laboratory of Vegetation Structure, Functions and Construction (VegLab), Kunming, Yunnan, China"}]},{"given":"Jie","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of International Rivers and 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