论文标题
Elmo和Bert在语义变化检测中的俄罗斯人
ELMo and BERT in semantic change detection for Russian
论文作者
论文摘要
我们研究上下文化嵌入的有效性，用于俄罗斯语言数据的简介语义变化检测任务。评估测试集由俄罗斯名词和形容词组成，根据苏联前，苏联和后苏联时期创建的文本中的出现。比较Elmo和Bert架构，根据其语义变化的程度随着时间的推移对俄罗斯的词进行排名。我们使用几种方法来汇总这些体系结构的上下文化嵌入并评估其性能。最后，我们在此任务中比较了无监督和监督的技术。
We study the effectiveness of contextualized embeddings for the task of diachronic semantic change detection for Russian language data. Evaluation test sets consist of Russian nouns and adjectives annotated based on their occurrences in texts created in pre-Soviet, Soviet and post-Soviet time periods. ELMo and BERT architectures are compared on the task of ranking Russian words according to the degree of their semantic change over time. We use several methods for aggregation of contextualized embeddings from these architectures and evaluate their performance. Finally, we compare unsupervised and supervised techniques in this task.
