AMI @ EVALITA2020:厌女症自动识别

E. Fersini, Debora Nozza, Paolo Rosso
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引用次数: 61

摘要

英语。厌女症自动识别(AMI)是在Evalita 2020评估活动中提出的一项共享任务。AMI挑战基于意大利语推文,分为两个子任务:(1)关于厌女症和攻击性识别的子任务A和(2)关于模型公平性的子任务B。在评估阶段结束时,我们总共收到了8个团队提交的子任务a的20次运行和子任务B的11次运行。本文概述了AMI共享任务、数据集、评估方法、参与者获得的结果,并讨论了团队采用的方法。最后,提出了一些结论,并对今后的工作进行了讨论。
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AMI @ EVALITA2020: Automatic Misogyny Identification
English. Automatic Misogyny Identification (AMI) is a shared task proposed at the Evalita 2020 evaluation campaign. The AMI challenge, based on Italian tweets, is organized into two subtasks: (1) Subtask A about misogyny and aggressiveness identification and (2) Subtask B about the fairness of the model. At the end of the evaluation phase, we received a total of 20 runs for Subtask A and 11 runs for Subtask B, submitted by 8 teams. In this paper, we present an overview of the AMI shared task, the datasets, the evaluation method-ology, the results obtained by the participants and a discussion about the method-ology adopted by the teams. Finally, we draw some conclusions and discuss future work.
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