基于语料库的修辞关系分析:词汇线索的研究

Taraneh Khazaei, Lu Xiao
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引用次数: 10

摘要

尽管计算语言学中的修辞结构理论(RST)有着悠久的传统,但目前还没有一种可靠的方法能够检测语篇中的修辞关系。为了为这种技术的发展铺平道路,我们开展了旨在了解使用基于语料库的词汇线索识别三种不同关系和两种不同文本类型的RST关系的有效性的实验。特别地,我们关注了CIRCUMSTANCE、EVALUATION和ELABORATION的三个关系以及两种不同的语料库:报纸文章和在线评论。分析结果表明,基于线索的方法可以有效地检测环境。然而,词汇线索在关系识别中的能力在精化中是有限的。在评价关系中,体裁特异性因素的作用更为显著。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Corpus-based analysis of rhetorical relations: A study of lexical cues
In spite of the long tradition of Rhetorical Structure Theory (RST) in computational linguistics, there is no robust method capable of detecting rhetorical relations in the text of discourse. To pave the way for development of such techniques, we carried out experiments aimed at understanding the effectiveness of using corpus-based lexical cues in the identification of RST relations for three different relations and across two different text genres. In particular, we focused on the three relations of CIRCUMSTANCE, EVALUATION, and ELABORATION and two different corpora: newspaper articles and online reviews. The analysis results indicate that the cue-based approaches can be quite effective in detecting CIRCUMSTANCE. However, the ability of lexical cues in relation identification is limited for ELABORATION. For the EVALUATION relation, genre-specific factors can play a more significant role.
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