In this article we present Enhanced Rhetorical Structure Theory (eRST), a new
theoretical framework for computational discourse analysis, based on an
expansion of Rhetorical Structure Theory (RST). The framework encompasses
discourse relation graphs with tree-breaking, nonprojective and concurrent
relations, as well as implicit and explicit signals which give explainable
rationales to our analyses. We survey shortcomings of RST and other existing
frameworks, such as Segmented Discourse Representation Theory (SDRT), the Penn
Discourse Treebank (PDTB) and Discourse Dependencies, and address these using
constructs in the proposed theory. We provide annotation, search and
visualization tools for data, and present and evaluate a freely available
corpus of English annotated according to our framework, encompassing 12 spoken
and written genres with over 200K tokens. Finally, we discuss automatic
parsing, evaluation metrics and applications for data in our framework.

我们提出了增强修辞结构理论（eRST），这是一种基于修辞结构理论（RST）扩展的计算化话语分析的新理论框架。该框架包括具有树破碎、非投射和并发关系的话语关系图，以及提供解释性的隐式和显式信号来解释我们的分析。我们调查了 RST 和其他现有框架的缺点，如分段话语表示理论（SDRT）、宾夕法尼亚话语树库（PDTB）和话语依赖，并使用所提出的理论中的构造来解决这些问题。我们为数据提供注释、搜索和可视化工具，并介绍和评估了一个根据我们的框架进行注释的英语语料库，包括 12 种口语和书面体样式，200,000 个单词。最后，我们讨论了在我们的框架中的数据自动解析、评估指标和应用。