论文标题
从有感知的数据中模拟词汇语义变化
Simulating Lexical Semantic Change from Sense-Annotated Data
论文作者
论文摘要
我们提出了一个新的程序，可以模拟同步识别数据的词汇语义变化，并证明了其在评估词汇语义变化检测模型中的有用性。与以前的合成数据集相比，诱导的数据集代表了与经验观察到的词法语义变化更强的对应关系，因为它利用了同步多义和毒理变化之间的亲密关系。我们发布数据，并为LSC检测模型提供第一个大规模评估金标准。
We present a novel procedure to simulate lexical semantic change from synchronic sense-annotated data, and demonstrate its usefulness for assessing lexical semantic change detection models. The induced dataset represents a stronger correspondence to empirically observed lexical semantic change than previous synthetic datasets, because it exploits the intimate relationship between synchronic polysemy and diachronic change. We publish the data and provide the first large-scale evaluation gold standard for LSC detection models.
