Contextualized word representations have proven useful for various natural language processing tasks. However, it remains unclear to what extent these representations can cover hand-coded semantic information such as semantic frames, which specify the semantic role of the arguments associated with a predicate. In this paper, we focus on verbs that evoke different frames depending on the context, and we investigate how well contextualized word representations can recognize the difference of frames that the same verb evokes. We also explore which types of representation are suitable for semantic frame induction. In our experiments, we compare seven different contextualized word representations for two English frame-semantic resources, FrameNet and PropBank. We demonstrate that several contextualized word representations, especially BERT and its variants, are considerably informative for semantic frame induction. Furthermore, we examine the extent to which the contextualized representation of a verb can estimate the number of frames that the verb can evoke.

本文研究了不同上下文环境下，有些动词引起的语义框架不同，以及如何利用Contextualized word representations识别这些不同的语义框架，同时探索哪些类型的表示适合用于语义框架的归纳。通过比较七种不同的Contextualized word representations，特别是BERT和其变体，在FrameNet和PropBank等英语Frame-semantic资源方面进行了实验，表明，某些Contextualized word representations对于语义框架的归纳具有相当的信息量。此外，本文还考察了动词的上下文表示估算其所引起的语义框架数的程度。

基于上下文化单词表示的动词意义聚类用于语义框架归纳