While our knowledge about ancient civilizations comes mostly from studies in archaeology and history books, much can also be learned or confirmed from literary texts. Using natural language processing techniques, we present aspects of ancient China as revealed by statistical textual analysis on the Complete Tang Poems, a 2.6-million-character corpus of all surviving poems from the Tang Dynasty (AD 618—907). Using an automatically created treebank of this corpus, we outline the semantic profiles of various poets, and discuss the role of s easons, geography, history, architecture, and colours, as observed through word selection and dependencies.