The Wenzi () is a Daoist classic allegedly written by a disciple of Laozi. The text was widely read and highly revered in the centuries following its creation, and even canonized as Tongxuan zhenjing () in the year 742 CE. However, soon afterwards scholars started questioning its authenticity and dismissing it as a forgery that was created between the Han dynasty and the Tang dynasty. The text's fate changed in 1973, when archeologists excavated a 55 BCE tomb and discovered remnants of a Wenzi copied on bamboo strips, which offer us a glimpse of what the text looked like prior to its drastic r
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The Wenzi () is a Daoist classic allegedly written by a disciple of Laozi. The text was widely read and highly revered in the centuries following its creation, and even canonized as Tongxuan zhenjing () in the year 742 CE. However, soon afterwards scholars started questioning its authenticity and dismissing it as a forgery that was created between the Han dynasty and the Tang dynasty. The text's fate changed in 1973, when archeologists excavated a 55 BCE tomb and discovered remnants of a Wenzi copied on bamboo strips, which offer us a glimpse of what the text looked like prior to its drastic revision into the current text.
==Author== thumb|page=81|Pages from a Ming dynasty printed edition of Wenzi The title Wenzi (; (zi) in this context meaning "master") is analogous with other Hundred Schools of Thought texts like Mozi, Zhuangzi, Guiguzi, and Baopuzi. Wen (meaning among other things "literature" or "culture") is a Chinese surname, and hence "Wenzi" is interpretable as "Master Wen." Wen is also frequently used in given names, posthumous names, et cetera, due to its positive connotations. For example, King Wen of Zhou (Analects 5.15). Hence, "Wenzi" could also be interpreted as a nom de plume denoting "Master of Literature/Culture." Nothing can be said for certain about the identity of Wenzi, no matter how this name is interpreted. Although we do not know his true identity, various hypotheses have been proposed.
Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).