Do sentence embeddings capture discourse properties of sentences from Scientific Abstracts ?

Laurine Huber, Chaker Memmadi, Mathilde Dargnat, Y. Toussaint
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引用次数: 2

Abstract

We introduce four tasks designed to determine which sentence encoders best capture discourse properties of sentences from scientific abstracts, namely coherence and cohesion between clauses of a sentence, and discourse relations within sentences. We show that even if contextual encoders such as BERT or SciBERT encodes the coherence in discourse units, they do not help to predict three discourse relations commonly used in scientific abstracts. We discuss what these results underline, namely that these discourse relations are based on particular phrasing that allow non-contextual encoders to perform well.
句子嵌入是否捕获了科学摘要中句子的话语属性?
我们介绍了四个任务,旨在确定哪些句子编码器最能捕获科学摘要句子的话语属性,即句子的子句之间的连贯性和凝聚力,以及句子内的话语关系。研究表明,即使BERT或SciBERT等语境编码器对语篇单位的连贯性进行编码,它们也无法预测科学摘要中常用的三种语篇关系。我们讨论了这些结果所强调的内容,即这些话语关系基于特定的措辞,这些措辞允许非上下文编码器表现良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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