Combining Language Models and Linguistic Information to Label Entities in Memes

Publication type
U
Publication status
Published
Authors
Singh, P., Maladry, A, & Lefever, E.
Series
Proceedings of the Workshop on Combating Online Hostile Posts in Regional Languages during Emergency Situations
Pagination
35-42
Publisher
Association for Computational Linguistics (Dublin, Ireland)
Conference
Second Workshop on Combating Online Hostile Posts in Regional Languages during Emergency Situation (Dublin, Ireland)
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Abstract

This paper describes the system we developed for the shared task “Hero, Villain and Victim: Dissecting harmful memes for Semantic role labeling of entities” organized in the frame- work of the Second Workshop on Combating Online Hostile Posts in Regional Languages during Emergency Situation (Constraint 2022). We present an ensemble approach combining transformer-based models and linguistic information, such as the presence of irony and implicit sentiment associated to the target named entities. The ensemble system obtains promising classification scores, with a macro F-score of 55%, resulting in a third place finish in the competition.