Solving and Generating Chinese Character Riddles

Abstract

Chinese character riddle is a riddle game in which the riddle solution is a single Chinese character. It is closely connected with the shape, pronunciation or meaning of Chinese characters. The riddle description (sentence) is usually composed of phrases with rich linguistic phenomena (such as pun, simile, and metaphor), which are associated to different parts (namely radicals) of the solution character. In this paper, we propose a statistical framework to solve and generate Chinese character riddles. Specifically, we learn the alignments and rules to identify the metaphors between phrases in riddles and radicals in characters. Then, in the solving phase, we utilize a dynamic programming method to combine the identified metaphors to obtain candidate solutions. In the riddle generation phase, we use a template-based method and a replacement-based method to obtain candidate riddle descriptions. We then use Ranking SVM to rerank the candidates both in the solving and generation process. Experimental results in the solving task show that the proposed method outperforms baseline methods. We also get very promising results in the generation task according to human judges.

BiRdQA: A Bilingual Dataset for Question Answering on Tricky Riddles

“…Chinese Riddle We exclude Chinese character riddles 21 , which have single Chinese characters as solutions and describe the structures of characters (Tan et al 2016). Instead we focus on common Chinese riddles which imply the meaning of the answer.…”

“…RiddleSense makes use of ConceptNet for distractor generation, which is potentially unfair for non-ConceptNetbased models and can limit future research directions19 . We further provide a detailed comparison of BiRdQA-en and RiddleSense in Appendix D Tan et al (2016). has studied on the solution and generation of Chinese character riddle, which present challenge regarding the structure of Chinese character rather than the meaning of the answer.…”

BiRdQA: A Bilingual Dataset for Question Answering on Tricky Riddles

“…5) RiddleSense makes use of ConceptNet for distractor generation, which is potentially unfair for non-ConceptNet-based models and thus restricts future research directions. Tan et al (2016) has studied on the solution and generation of Chinese character riddle, which present challenge regarding the structure of Chinese character rather than the meaning of the answer. But BiRdQA-zh explicitly excludes this type of Chinese riddle.…”

RiddleSense: Reasoning about Riddle Questions Featuring Linguistic Creativity and Commonsense Knowledge

“…Riddling, as a way to use creative descriptions to query a common concept, are relatively underexplored. Previous works (Tan et al, 2016;Gonc ¸alo Oliveira and Rodrigues, 2018) focus on the generation of riddles in specific languages and usually rely on language-specific features (e.g., decomposing a Chinese character into multiple smaller pieces). There is few datasets or public resources for studying riddles as a reasoning task, to the best of our knowledge.…”