Neural recovery machine for Chinese dropped pronoun

• Published in: Frontiers of Computer Science Vol. 13; no. 5; pp. 1023 - 1033
• Main Authors: ZHANG, Weinan, LIU, Ting, YIN, Qingyu, ZHANG, Yu
• Format: Journal Article
• Language: English
• Published: Beijing Higher Education Press 01-10-2019; Springer Nature B.V
• Subjects: Annotations; Chinese dropped pronoun recovery; Chinese zero pronoun resolution; Computer Science; Datasets; Natural language; neural network; Recovery; Research Article; Snow; Translations; neural network; Chinese zero pronoun resolution; Chinese dropped pronoun recovery
• ISSN: 2095-2228; 2095-2236
• DOI: 10.1007/s11704-018-7136-7

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.