Summary of Cmdag: a Chinese Metaphor Dataset with Annotated Grounds As Cot For Boosting Metaphor Generation, by Yujie Shao et al.
CMDAG: A Chinese Metaphor Dataset with Annotated Grounds as CoT for Boosting Metaphor Generation
by Yujie Shao, Xinrong Yao, Xingwei Qu, Chenghua Lin, Shi Wang, Stephen W. Huang, Ge Zhang, Jie Fu
First submitted to arxiv on: 20 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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Summary difficulty | Written by | Summary |
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High | Paper authors | High Difficulty Summary Read the original abstract here |
Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper introduces a large-scale, high-quality annotated Chinese Metaphor Corpus, comprising 28K sentences from various literary sources. The corpus is designed to facilitate research on Chinese metaphors, with guidelines for accurate and consistent annotations. By focusing on “grounds” as Chain of Thoughts inputs, the authors generate metaphors that better resonate with real-world intuition. They test generative models like Belle, Baichuan, and Chinese-alpaca-33B using their annotated corpus, demonstrating its value in Chinese metaphor research. |
Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a big collection of Chinese phrases that use metaphors. A metaphor is when you say something is like something else, but they’re not really the same thing. For example, “He’s a shining star” means someone is very good at something. The authors want to make it easier for people to study and create new metaphors in Chinese by giving them a big list of existing ones that are labeled as correct or incorrect. They also try to come up with new metaphors using these labeled phrases, and they test how well different computer programs can do this task. |