论文标题
Semeval-2020任务1：无监督的词汇更改检测
SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection
论文作者
论文摘要
词汇语义变化检测，即识别随时间变化含义的单词的任务是一个非常活跃的研究领域，在NLP，词典和语言学中的应用。评估目前是词汇语义变化检测中最紧迫的问题，因为社区没有金标准，这阻碍了进步。我们通过为研究人员提供评估框架和手动注释，英语，德语，拉丁语和瑞典语的高质量数据集，介绍第一个共享任务的结果，该任务的结果解决了这一差距。 33个团队提交了186个系统，并在两个子任务上进行了评估。
Lexical Semantic Change detection, i.e., the task of identifying words that change meaning over time, is a very active research area, with applications in NLP, lexicography, and linguistics. Evaluation is currently the most pressing problem in Lexical Semantic Change detection, as no gold standards are available to the community, which hinders progress. We present the results of the first shared task that addresses this gap by providing researchers with an evaluation framework and manually annotated, high-quality datasets for English, German, Latin, and Swedish. 33 teams submitted 186 systems, which were evaluated on two subtasks.
