  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.
