TY - GEN
T1 - ECNU_ICA at SemEval-2022 Task 10
T2 - 16th International Workshop on Semantic Evaluation, SemEval 2022, co-located (hybrid) with The 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics, NAACL 2022
AU - Zhang, Qi
AU - Zhou, Jie
AU - Chen, Qin
AU - Bai, Qingchun
AU - Xiao, Jun
AU - He, Liang
N1 - Publisher Copyright:
© 2022 Association for Computational Linguistics.
PY - 2022
Y1 - 2022
N2 - In this paper, we focus on the structured sentiment analysis task that is released on SemEval-2022 Task 10. The task aims to extract the structured sentiment information (e.g., holder, target, expression and sentiment polarity) in a text. We propose a simple and unified model for both the monolingual and crosslingual structured sentiment analysis tasks. We translate this task into an event extraction task by regarding the expression as the trigger word and the other elements as the arguments of the event. Particularly, we first extract the expression by judging its start and end indices. Then, to consider the expression, we design a conditional layer normalization algorithm to extract the holder and target based on the extracted expression. Finally, we infer the sentiment polarity based on the extracted structured information. We conduct the experiments on seven datasets in five languages. It attracted 233 submissions in monolingual subtask and crosslingual subtask from 32 teams. Finally, we obtain the top 5 place on crosslingual tasks.
AB - In this paper, we focus on the structured sentiment analysis task that is released on SemEval-2022 Task 10. The task aims to extract the structured sentiment information (e.g., holder, target, expression and sentiment polarity) in a text. We propose a simple and unified model for both the monolingual and crosslingual structured sentiment analysis tasks. We translate this task into an event extraction task by regarding the expression as the trigger word and the other elements as the arguments of the event. Particularly, we first extract the expression by judging its start and end indices. Then, to consider the expression, we design a conditional layer normalization algorithm to extract the holder and target based on the extracted expression. Finally, we infer the sentiment polarity based on the extracted structured information. We conduct the experiments on seven datasets in five languages. It attracted 233 submissions in monolingual subtask and crosslingual subtask from 32 teams. Finally, we obtain the top 5 place on crosslingual tasks.
UR - https://www.scopus.com/pages/publications/85137591828
U2 - 10.18653/v1/2022.semeval-1.186
DO - 10.18653/v1/2022.semeval-1.186
M3 - 会议稿件
AN - SCOPUS:85137591828
T3 - SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop
SP - 1336
EP - 1342
BT - SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop
A2 - Emerson, Guy
A2 - Schluter, Natalie
A2 - Stanovsky, Gabriel
A2 - Kumar, Ritesh
A2 - Palmer, Alexis
A2 - Schneider, Nathan
A2 - Singh, Siddharth
A2 - Ratan, Shyam
PB - Association for Computational Linguistics (ACL)
Y2 - 14 July 2022 through 15 July 2022
ER -