MCTS: A Multi-Reference Chinese Text Simplification Dataset
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866913378423799808 |
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| author | Chong, Ruining Lu, Luming Yang, Liner Nie, Jinran Liu, Zhenghao Wang, Shuo Zhou, Shuhan Li, Yaoxin Yang, Erhong |
| author_facet | Chong, Ruining Lu, Luming Yang, Liner Nie, Jinran Liu, Zhenghao Wang, Shuo Zhou, Shuhan Li, Yaoxin Yang, Erhong |
| contents | Text simplification aims to make the text easier to understand by applying rewriting transformations. There has been very little research on Chinese text simplification for a long time. The lack of generic evaluation data is an essential reason for this phenomenon. In this paper, we introduce MCTS, a multi-reference Chinese text simplification dataset. We describe the annotation process of the dataset and provide a detailed analysis. Furthermore, we evaluate the performance of several unsupervised methods and advanced large language models. We additionally provide Chinese text simplification parallel data that can be used for training, acquired by utilizing machine translation and English text simplification. We hope to build a basic understanding of Chinese text simplification through the foundational work and provide references for future research. All of the code and data are released at https://github.com/blcuicall/mcts/. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_02796 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | MCTS: A Multi-Reference Chinese Text Simplification Dataset Chong, Ruining Lu, Luming Yang, Liner Nie, Jinran Liu, Zhenghao Wang, Shuo Zhou, Shuhan Li, Yaoxin Yang, Erhong Computation and Language Text simplification aims to make the text easier to understand by applying rewriting transformations. There has been very little research on Chinese text simplification for a long time. The lack of generic evaluation data is an essential reason for this phenomenon. In this paper, we introduce MCTS, a multi-reference Chinese text simplification dataset. We describe the annotation process of the dataset and provide a detailed analysis. Furthermore, we evaluate the performance of several unsupervised methods and advanced large language models. We additionally provide Chinese text simplification parallel data that can be used for training, acquired by utilizing machine translation and English text simplification. We hope to build a basic understanding of Chinese text simplification through the foundational work and provide references for future research. All of the code and data are released at https://github.com/blcuicall/mcts/. |
| title | MCTS: A Multi-Reference Chinese Text Simplification Dataset |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2306.02796 |