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Neural recovery machine for Chinese dropped pronoun

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Abstract

Dropped pronouns (DPs) are ubiquitous in prodrop languages like Chinese, Japanese etc. Previous work mainly focused on painstakingly exploring the empirical features for DPs recovery. In this paper, we propose a neural recovery machine (NRM) to model and recover DPs in Chinese to avoid the non-trivial feature engineering process. The experimental results show that the proposed NRM significantly outperforms the state-of-the-art approaches on two heterogeneous datasets. Further experimental results of Chinese zero pronoun (ZP) resolution show that the performance of ZP resolution can also be improved by recovering the ZPs to DPs.

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Acknowledgements

This paper was supported by the National Natural Science Foundation of China (Grant Nos. 61502120, 61472105, 61772153), Heilongjiang philosophy and social science research project (16TQD03), Young research foundation of Harbin University (HUYF2013-002), the project of university library work committee of Heilongjiang (2013-B-065).

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Correspondence to Ting Liu.

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Weinan Zhang is a Lecturer in Research Center for Social Computing and Information Retrieval, School of Computer Science and Technology, Harbin Institute of Technology, China. His research interest includes human-computer dialogue, natural language processing and information retrieval.

Ting Liu is a professor in Research Center for Social Computing and Information Retrieval, School of Computer Science and Technology, Harbin Institute of Technology, China. His primary research interest is natural language processing, information retrieval and social computing.

Qingyu Yin is a PhD student in Research Center for Social Computing and Information Retrieval, School of Computer Science and Technology, Harbin Institute of Technology, China. His research interest is anaphora resolution and natural language processing.

Yu Zhang is a professor in Research Center for Social Computing and Information Retrieval, School of Computer Science and Technology, Harbin Institute of Technology, China. His primary research interest is question answering, natural language processing and information retrieval.

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Zhang, W., Liu, T., Yin, Q. et al. Neural recovery machine for Chinese dropped pronoun. Front. Comput. Sci. 13, 1023–1033 (2019). https://doi.org/10.1007/s11704-018-7136-7

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