We present the first shared task on semantic change discovery and detection in Spanish and create the first dataset of Spanish words manually annotated for semantic change using the DURel framework (Schlechtweg et al., 2018). The task is divided in two phases: 1) Graded Change Discovery, and 2) Binary Change Detection. In addition to introducing a new language the main novelty with respect to the previous tasks consists in predicting and evaluating changes for all vocabulary words in the corpus. Six teams participated in phase 1 and seven teams in phase 2 of the shared task, and the best system obtained a Spearman rank correlation of 0.735 for phase 1 and an F1 score of 0.716 for phase 2. We describe the systems developed by the competing teams, highlighting the techniques that were particularly useful and discuss the limits of these approaches.

翻译：我们用西班牙文提出了第一个关于语义变化发现和探测的共同任务,并用DURel框架(Schlechtweg等人,2018年)为语义变化人工附加说明,创建了第一个西班牙文词组数据集。任务分为两个阶段:1) 等级变化发现,2) 二进制变化检测。除了采用新语言外,与以前任务有关的主要新颖之处是预测和评价本体中所有词汇词句的变化。六个小组参加了第一阶段,七个小组参加了第二阶段的共享任务,最佳系统获得了第一阶段Spearman等级为0.735的比值,第2阶段为0.716的F1分。我们描述了各竞争小组开发的系统,强调了特别有用的技术,并讨论了这些方法的局限性。