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.
CITATION STYLE
Li, J., Bao, Y., Huang, S., Dai, X., & Chen, J. (2020). Explicit semantic decomposition for definition generation. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 708–717). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2020.acl-main.65
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