论文标题
LSCDISCOVERY：西班牙语中关于语义变化发现和检测的共同任务
LSCDiscovery: A shared task on semantic change discovery and detection in Spanish
论文作者
论文摘要
我们介绍了西班牙语中的语义变化发现和检测的第一个共享任务，并创建了第一个使用Durel框架手动注释语义变化的西班牙语单词的数据集（Schlechtweg等，2018）。该任务分为两个阶段：1）分级变化发现，以及2）二进制变更检测。除了引入一种新语言外，关于先前任务的主要新颖性还包括预测和评估语料库中所有词汇单词的变化。六支球队参加了共享任务的第2阶段和七个团队，最佳系统获得了Spearman等级的相关性为0.735，而第2阶段的F1得分为0.716。我们描述了竞争团队开发的系统，突出了这些技术的技术，这些技术特别有用，并讨论了这些方法的限制。
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.
