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The Chinese character riddle is a unique form of cultural entertainmentspecific to the Chinese language. It typically comprises two parts: the riddledescription and the solution. The solution to the riddle is a single character,while the riddle description primarily describes the glyph of the solution,occasionally supplemented with its explanation and pronunciation. SolvingChinese character riddles is a challenging task that demands understanding ofcharacter glyph, general knowledge, and a grasp of figurative language. In thispaper, we construct a \textbf{C}hinese \textbf{C}haracter riddle dataset namedCC-Riddle, which covers the majority of common simplified Chinese characters.The construction process is a combination of web crawling, language modelgeneration and manual filtering. In generation stage, we input the Chinesephonetic alphabet, glyph and meaning of the solution character into thegeneration model, which then produces multiple riddle descriptions. Thegenerated riddles are then manually filtered and the final CC-Riddle dataset iscomposed of both human-written riddles and these filtered, generated riddles.In order to assess the performance of language models on the task of solvingcharacter riddles, we use retrieval-based, generative and multiple-choice QAstrategies to test three language models: BERT, ChatGPT and ChatGLM. The testresults reveal that current language models still struggle to solve Chinesecharacter riddles. CC-Riddle is publicly available at\url{https://github.com/pku0xff/CC-Riddle}.

CC-Riddle: A Question Answering Dataset of Chinese Character Riddles