论文标题
多语言BERT中的单词订单类型：下属子句检测中的案例研究
Word-order typology in Multilingual BERT: A case study in subordinate-clause detection
论文作者
论文摘要
在学习句法抽象时，特别是跨语言，BERT和类似模型的功能和局限性仍不清楚。在本文中，我们使用在语言内和跨语言内和跨语言内的下句检测的任务来探测这些属性。我们表明，这项任务在看似简单，轻松的收益被较硬的案例的长尾巴所抵消，而伯特的零射击性能则由单词顺序效应主导，反映了SVO/VSO/SOV类型。
The capabilities and limitations of BERT and similar models are still unclear when it comes to learning syntactic abstractions, in particular across languages. In this paper, we use the task of subordinate-clause detection within and across languages to probe these properties. We show that this task is deceptively simple, with easy gains offset by a long tail of harder cases, and that BERT's zero-shot performance is dominated by word-order effects, mirroring the SVO/VSO/SOV typology.
