StoryAnalogy: Deriving Story-level Analogies from Large Language Models to Unlock Analogical Understanding

This repo contains the dataset and code in the EMNLP'23 paper: StoryAnalogy: Deriving Story-level Analogies from Large Language Models to Unlock Analogical Understanding.

An example analogy between story S1 and S2.

Use StoryAnalogy

We recommend using Hugging Face's datasets to load the story analogy dataset:

from datasets import load_dataset

dataset = load_dataset("JoeyCheng/story_analogy")

The multiple choice subset can be found at src/data/storyanalogy_multiple_choice.json.

Misc

If you have any questions related to the code or the paper, please feel free to email us at [email protected].

If you use this research, please cite us:

@inproceedings{jiayang2023storyanalogy,
  title={StoryAnalogy: Deriving Story-level Analogies from Large Language Models to Unlock Analogical Understanding},
  author={Jiayang, Cheng and Qiu, Lin and Chan, Tsz and Fang, Tianqing and Wang, Weiqi and Chan, Chunkit and Ru, Dongyu and Guo, Qipeng and Zhang, Hongming and Song, Yangqiu and others},
  booktitle={Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing},
  pages={11518--11537},
  year={2023}
}