Explicit Semantic Decomposition for Definition Generation
Jiahuan Li, Yu Bao, Shujian Huang, Xinyu Dai, Jiajun Chen
Abstract
Definition generation, which aims to automatically generate dictionary definitions for words, has recently been proposed to assist the construction of dictionaries and help people understand unfamiliar texts. However, previous works hardly consider explicitly modeling the "components" of definitions, leading to under-specific generation results. In this paper, we propose ESD, namely Explicit Semantic Decomposition for definition generation, which explicitly decomposes meaning of words into semantic components, and models them with discrete latent variables for definition generation. Experimental results show that ESD achieves substantial improvements on WordNet and Oxford benchmarks over strong previous baselines.
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- Understanding Jargon: Combining Extraction and Generation for Definition ModelingJie Huang, Hanyin Shao, Kevin Chen-Chuan Chang, Jinjun Xiong et al.EMNLP 2022 · 11 citations
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- Definition Modelling for Appropriate SpecificityHan Huang, Tomoyuki Kajiwara, Yuki AraseEMNLP 2021
- Can Large Language Models Understand Internet Buzzwords Through User-Generated ContentChen Huang, Junkai Luo, Xinzuo Wang, Wenqiang Lei et al.ACL 2025
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