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Correcting the Misuse: A Method for the Chinese Idiom Cloze Test

Authors :
Hongbo Wang
Tan Yang
Hongsheng Zhao
Xinyu Wang
Source :
Proceedings of Deep Learning Inside Out (DeeLIO): The First Workshop on Knowledge Extraction and Integration for Deep Learning Architectures.
Publication Year :
2020
Publisher :
Association for Computational Linguistics, 2020.

Abstract

The cloze test for Chinese idioms is a new challenge in machine reading comprehension: given a sentence with a blank, choosing a candidate Chinese idiom which matches the context. Chinese idiom is a type of Chinese idiomatic expression. The common misuse of Chinese idioms leads to error in corpus and causes error in the learned semantic representation of Chinese idioms. In this paper, we introduce the definition written by Chinese experts to correct the misuse. We propose a model for the Chinese idiom cloze test integrating various information effectively. We propose an attention mechanism called Attribute Attention to balance the weight of different attributes among different descriptions of the Chinese idiom. Besides the given candidates of every blank, we also try to choose the answer from all Chinese idioms that appear in the dataset as the extra loss due to the uniqueness and specificity of Chinese idioms. In experiments, our model outperforms the state-of-the-art model.

Details

Database :
OpenAIRE
Journal :
Proceedings of Deep Learning Inside Out (DeeLIO): The First Workshop on Knowledge Extraction and Integration for Deep Learning Architectures
Accession number :
edsair.doi...........35412e9aba1d4865151446d6614ed373
Full Text :
https://doi.org/10.18653/v1/2020.deelio-1.1