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2021 | OriginalPaper | Buchkapitel

A Dual-Attention Neural Network for Pun Location and Using Pun-Gloss Pairs for Interpretation

verfasst von : Shen Liu, Meirong Ma, Hao Yuan, Jianchao Zhu, Yuanbin Wu, Man Lan

Erschienen in: Natural Language Processing and Chinese Computing

Verlag: Springer International Publishing

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Abstract

Pun location is to identify the punning word (usually a word or a phrase that makes the text ambiguous) in a given short text, and pun interpretation is to find out two different meanings of the punning word. Most previous studies adopt limited word senses obtained by WSD(Word Sense Disambiguation) technique or pronunciation information in isolation to address pun location. For the task of pun interpretation, related work pays attention to various WSD algorithms. In this paper, a model called DANN (Dual-Attentive Neural Network) is proposed for pun location, effectively integrates word senses and pronunciation with context information to address two kinds of pun at the same time. Furthermore, we treat pun interpretation as a classification task and construct pun-gloss pairs as processing data to solve this task. Experiments on the two benchmark datasets show that our proposed methods achieve new state-of-the-art results. Our source code is available in the public code repository (https://github.com/LawsonAbs/pun).

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Titel: A Dual-Attention Neural Network for Pun Location and Using Pun-Gloss Pairs for Interpretation
verfasst von: Shen Liu
Meirong Ma
Hao Yuan
Jianchao Zhu
Yuanbin Wu
Man Lan
Verlag: Springer International Publishing
Buch: Natural Language Processing and Chinese Computing
Print ISBN: 978-3-030-88479-6

Electronic ISBN: 978-3-030-88480-2

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-88480-2_55

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