Tourism　knowledge　graphs　lack　cultural　content,　limiting　their　usefulness　for　cultural　tourists.This　paper　presents　the　development　of　a　cultural　perspective-based　knowledge　graph　(CuPe-KG).　We　evaluated　fine-tuning　ERNIE　3.0　(FT-ERNIE)　and　ChatGPT　for　cultural　type　recognition　to　strengthen　the　relationship　between　tourism　resources　and　cultures.　Our　investigation　used　an　annotated　cultural　tourism　resource　dataset　containing　2,745　items　across　16　cultural　types.　The　results　showed　accuracy　scores　for　FT-ERNIE　and　ChatGPT　of　0.81　and　0.12,　respectively,　with　FT-ERNIE　achieving　a　micro-F1　score　of　0.93,　a　26　percentage　point　lead　over　ChatGPT＇s　score　of　0.67.　These　underscore　FT-ERNIE＇s　superior　performance　(the　shortcoming　is　the　need　to　annotate　data)　while　highlighting　ChatGPT＇s　limitations　because　of　insufficient　Chinese　training　data　and　lower　identification　accuracy　in　professional　knowledge.　A　novel　ontology　was　designed　to　facilitate　the　construction　of　CuPe-KG,　including　elements　such　as　cultural　types,　historical　figures,　events,　and　intangible　cultural　heritage.　CuPe-KG　effectively　addresses　cultural　tourism　visitors’　information　retrieval　needs.　©　2024