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CCD-ASQP: A Chinese Cross-Domain Aspect Sentiment Quadruple Prediction Dataset

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Knowledge Graph and Semantic Computing: Knowledge Graph Empowers Artificial General Intelligence (CCKS 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1923))

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Abstract

This work present CCD-ASQP, a cross-domain Aspect Sentiment Quadruple prediction(ASQP) dataset in chinese. Based on e-commerce scenario, this dataset lables 15,878 sentiment quadruples out of 3,700 reviews across 6 life domain and 10 product entities. Multiple baselines have been test on CCD-ASQP in terms of ASQP task, and performances have been compared with ChatGPT. Deep learning models’ dramatic decline of accuracy of when shifting to out-of-distribution data shows the lack of domain adaptiveness. ChatGPT achieves relatively consistent cross-domain performance in few-shot setup. Error analysis suggests effect of Chinese language forms on ASQP task. CCD-ASQP leaves great space for sentiment analysis tasks in Chinese language and perspectives from other disciplines are helpful.

The dataset can be obtained from https://github.com/blcunlp/CCD-ASQP.

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Notes

  1. 1.

    The “aspect category” and “sentient polarity” items were accurately matched, while the “aspect term” and “opinion” items were fuzzily matched, that is, they are correct as long as they contain key information.

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Acknowledgement

This research project is supported by Science Foundation of Beijing Language and Culture University (supported by “the Fundamental Research Funds for the Central Universities”) (23YJ080009).

Author information

Authors and Affiliations

  1. Beijing Language and Culture University, Beijing, China

    Ye Wang, Yuan Zhong, Xu Zhang, Conghui Niu, Dong Yu & Pengyuan Liu

  2. National Language Resources Monitoring and Research Center for Print Media, Beijing, China

    Pengyuan Liu

Authors
  1. Ye Wang
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  2. Yuan Zhong
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  3. Xu Zhang
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  4. Conghui Niu
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  5. Dong Yu
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  6. Pengyuan Liu
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Corresponding author

Correspondence to Pengyuan Liu .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    Haofen Wang

  2. Chinese Academy of Sciences, Beijing, China

    Xianpei Han

  3. Harbin Institute of Technology, Harbin, China

    Ming Liu

  4. Nanjing University, Nanjing, China

    Gong Cheng

  5. University of South China, Hengyang, China

    Yongbin Liu

  6. Zhejiang University, Hangzhou, China

    Ningyu Zhang

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Wang, Y., Zhong, Y., Zhang, X., Niu, C., Yu, D., Liu, P. (2023). CCD-ASQP: A Chinese Cross-Domain Aspect Sentiment Quadruple Prediction Dataset. In: Wang, H., Han, X., Liu, M., Cheng, G., Liu, Y., Zhang, N. (eds) Knowledge Graph and Semantic Computing: Knowledge Graph Empowers Artificial General Intelligence. CCKS 2023. Communications in Computer and Information Science, vol 1923. Springer, Singapore. https://doi.org/10.1007/978-981-99-7224-1_18

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  • DOI: https://doi.org/10.1007/978-981-99-7224-1_18

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  • Online ISBN: 978-981-99-7224-1

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