%0 Conference Proceedings %T Zero Pronouns Identification based on Span prediction %A Iwata, Sei %A Watanabe, Taro %A Nagata, Masaaki %Y Kabbara, Jad %Y Lin, Haitao %Y Paullada, Amandalynne %Y Vamvas, Jannis %S Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Student Research Workshop %D 2021 %8 August %I Association for Computational Linguistics %C Online %F iwata-etal-2021-zero %X The presence of zero-pronoun (ZP) greatly affects the downstream tasks of NLP in pro-drop languages such as Japanese and Chinese. To tackle the problem, the previous works identified ZPs as sequence labeling on the word sequence or the linearlized tree nodes of the input. We propose a novel approach to ZP identification by casting it as a query-based argument span prediction task. Given a predicate as a query, our model predicts the omission with ZP. In the experiments, our model surpassed the sequence labeling baseline. %R 10.18653/v1/2021.acl-srw.34 %U https://aclanthology.org/2021.acl-srw.34 %U https://doi.org/10.18653/v1/2021.acl-srw.34 %P 331-336