This paper describes the SemEval-2020 shared task "Assessing Humor in Edited
News Headlines." The task's dataset contains news headlines in which short
edits were applied to make them funny, and the funniness of these edited
headlines was rated using crowdsourcing. This task includes two subtasks, the
first of which is to estimate the funniness of headlines on a humor scale in
the interval 0-3. The second subtask is to predict, for a pair of edited
versions of the same original headline, which is the funnier version. To date,
this task is the most popular shared computational humor task, attracting 48
teams for the first subtask and 31 teams for the second.

本文讲述了 SemEval-2020 共享任务 “评估编辑新闻标题中的幽默”。任务的数据集包含应用了简短编辑使其有趣的新闻标题，这些编辑后的标题的有趣程度使用众包评级。该任务包括两个子任务，第一个是在 0-3 区间的幽默等级上估计标题的幽默程度。第二个子任务是为同一原始标题的一对编辑版本预测哪个更有趣。迄今为止，这是最受欢迎的共享计算幽默任务，吸引了 48 个团队参加第一个子任务和 31 个团队参加第二个子任务。