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    <abstract>Opinion Role Labeling (ORL), aiming to identify the key roles of opinion, has received increasing interest. Unlike most of the previous works focusing on the English language, in this paper, we present the first work of Chinese ORL. We construct a Chinese dataset by manually translating and projecting annotations from a standard English MPQA dataset. Then, we investigate the effectiveness of cross-lingual transfer methods, including model transfer and corpus translation. We exploit multilingual BERT with Contextual Parameter Generator and Adapter methods to examine the potentials of unsupervised cross-lingual learning and our experiments and analyses for both bilingual and multilingual transfers establish a foundation for the future research of this task.</abstract>
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%0 Conference Proceedings
%T Chinese Opinion Role Labeling with Corpus Translation: A Pivot Study
%A Zhen, Ranran
%A Wang, Rui
%A Fu, Guohong
%A Lv, Chengguo
%A Zhang, Meishan
%Y Moens, Marie-Francine
%Y Huang, Xuanjing
%Y Specia, Lucia
%Y Yih, Scott Wen-tau
%S Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
%D 2021
%8 November
%I Association for Computational Linguistics
%C Online and Punta Cana, Dominican Republic
%F zhen-etal-2021-chinese
%X Opinion Role Labeling (ORL), aiming to identify the key roles of opinion, has received increasing interest. Unlike most of the previous works focusing on the English language, in this paper, we present the first work of Chinese ORL. We construct a Chinese dataset by manually translating and projecting annotations from a standard English MPQA dataset. Then, we investigate the effectiveness of cross-lingual transfer methods, including model transfer and corpus translation. We exploit multilingual BERT with Contextual Parameter Generator and Adapter methods to examine the potentials of unsupervised cross-lingual learning and our experiments and analyses for both bilingual and multilingual transfers establish a foundation for the future research of this task.
%R 10.18653/v1/2021.emnlp-main.796
%U https://aclanthology.org/2021.emnlp-main.796
%U https://doi.org/10.18653/v1/2021.emnlp-main.796
%P 10139-10149

Markdown (Informal)

[Chinese Opinion Role Labeling with Corpus Translation: A Pivot Study](https://aclanthology.org/2021.emnlp-main.796) (Zhen et al., EMNLP 2021)

• Chinese Opinion Role Labeling with Corpus Translation: A Pivot Study (Zhen et al., EMNLP 2021)

ACL

• Ranran Zhen, Rui Wang, Guohong Fu, Chengguo Lv, and Meishan Zhang. 2021. Chinese Opinion Role Labeling with Corpus Translation: A Pivot Study. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 10139–10149, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.