Chinese Lexical Simplification

• URL: http://arxiv.org/abs/2010.07048v1
• Date: Wed, 14 Oct 2020 12:55:36 GMT
• Title: Chinese Lexical Simplification
• Authors: Jipeng Qiang and Xinyu Lu and Yun Li and Yunhao Yuan and Yang Shi and Xindong Wu
• Abstract summary: There is no research work for Chinese lexical simplification ( CLS) task. To circumvent difficulties in acquiring annotations, we manually create the first benchmark dataset for CLS. We present five different types of methods as baselines to generate substitute candidates for the complex word.
• Score: 29.464388721085548
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Lexical simplification has attracted much attention in many languages, which is the process of replacing complex words in a given sentence with simpler alternatives of equivalent meaning. Although the richness of vocabulary in Chinese makes the text very difficult to read for children and non-native speakers, there is no research work for Chinese lexical simplification (CLS) task. To circumvent difficulties in acquiring annotations, we manually create the first benchmark dataset for CLS, which can be used for evaluating the lexical simplification systems automatically. In order to acquire more thorough comparison, we present five different types of methods as baselines to generate substitute candidates for the complex word that include synonym-based approach, word embedding-based approach, pretrained language model-based approach, sememe-based approach, and a hybrid approach. Finally, we design the experimental evaluation of these baselines and discuss their advantages and disadvantages. To our best knowledge, this is the first study for CLS task.

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