@inproceedings{zheng-etal-2021-decompose,
title = "Decompose, Fuse and Generate: A Formation-Informed Method for {C}hinese Definition Generation",
author = "Zheng, Hua and
Dai, Damai and
Li, Lei and
Liu, Tianyu and
Sui, Zhifang and
Chang, Baobao and
Liu, Yang",
editor = "Toutanova, Kristina and
Rumshisky, Anna and
Zettlemoyer, Luke and
Hakkani-Tur, Dilek and
Beltagy, Iz and
Bethard, Steven and
Cotterell, Ryan and
Chakraborty, Tanmoy and
Zhou, Yichao",
booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.naacl-main.437",
doi = "10.18653/v1/2021.naacl-main.437",
pages = "5524--5531",
abstract = "In this paper, we tackle the task of Definition Generation (DG) in Chinese, which aims at automatically generating a definition for a word. Most existing methods take the source word as an indecomposable semantic unit. However, in parataxis languages like Chinese, word meanings can be composed using the word formation process, where a word ({``}桃花{''}, peach-blossom) is formed by formation components ({``}桃{''}, peach; {``}花{''}, flower) using a formation rule (Modifier-Head). Inspired by this process, we propose to enhance DG with word formation features. We build a formation-informed dataset, and propose a model DeFT, which Decomposes words into formation features, dynamically Fuses different features through a gating mechanism, and generaTes word definitions. Experimental results show that our method is both effective and robust.",
}
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<abstract>In this paper, we tackle the task of Definition Generation (DG) in Chinese, which aims at automatically generating a definition for a word. Most existing methods take the source word as an indecomposable semantic unit. However, in parataxis languages like Chinese, word meanings can be composed using the word formation process, where a word (“桃花”, peach-blossom) is formed by formation components (“桃”, peach; “花”, flower) using a formation rule (Modifier-Head). Inspired by this process, we propose to enhance DG with word formation features. We build a formation-informed dataset, and propose a model DeFT, which Decomposes words into formation features, dynamically Fuses different features through a gating mechanism, and generaTes word definitions. Experimental results show that our method is both effective and robust.</abstract>
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%0 Conference Proceedings
%T Decompose, Fuse and Generate: A Formation-Informed Method for Chinese Definition Generation
%A Zheng, Hua
%A Dai, Damai
%A Li, Lei
%A Liu, Tianyu
%A Sui, Zhifang
%A Chang, Baobao
%A Liu, Yang
%Y Toutanova, Kristina
%Y Rumshisky, Anna
%Y Zettlemoyer, Luke
%Y Hakkani-Tur, Dilek
%Y Beltagy, Iz
%Y Bethard, Steven
%Y Cotterell, Ryan
%Y Chakraborty, Tanmoy
%Y Zhou, Yichao
%S Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
%D 2021
%8 June
%I Association for Computational Linguistics
%C Online
%F zheng-etal-2021-decompose
%X In this paper, we tackle the task of Definition Generation (DG) in Chinese, which aims at automatically generating a definition for a word. Most existing methods take the source word as an indecomposable semantic unit. However, in parataxis languages like Chinese, word meanings can be composed using the word formation process, where a word (“桃花”, peach-blossom) is formed by formation components (“桃”, peach; “花”, flower) using a formation rule (Modifier-Head). Inspired by this process, we propose to enhance DG with word formation features. We build a formation-informed dataset, and propose a model DeFT, which Decomposes words into formation features, dynamically Fuses different features through a gating mechanism, and generaTes word definitions. Experimental results show that our method is both effective and robust.
%R 10.18653/v1/2021.naacl-main.437
%U https://aclanthology.org/2021.naacl-main.437
%U https://doi.org/10.18653/v1/2021.naacl-main.437
%P 5524-5531
Markdown (Informal)
[Decompose, Fuse and Generate: A Formation-Informed Method for Chinese Definition Generation](https://aclanthology.org/2021.naacl-main.437) (Zheng et al., NAACL 2021)
ACL