Research on Question Answering is focused mainly on classifying the question type and finding the answer. Presenting the answer in a way that suits the user’s needs has received little attention. This paper shows how existing question answering systems—which aim at finding precise answers to questions—can be improved by exploiting summarization techniques to extract more than just the answer fr...

We describe the design, development, and API for two discourse parsers for Rhetorical Structure Theory. The two parsers use the same underlying framework, but one uses features that rely on dependency syntax, produced by a fast shift-reduce parser, whereas the other uses a richer feature space, including both constituentand dependency-syntax and coreference information, produced by the Stanford...

To understand a discourse the reader needs to recover the relations between the discourse elements as intended by the writer Writers can and very often do help the reader along by providing explicit lexical signals of the intended discourse relations through the use of lexicalised discourse markers In this paper we present a novel approach for generating texts containing multiple embedded rheto...

The Text2Dialogue (T2D) system that we are developing allows digital content creators to generate attractive multi-modal dialogues presented by two virtual agents—by simply providing textual information as input. We use Rhetorical Structure Theory (RST) to decompose text into segments and to identify rhetorical discourse relations between them. These are then “acted out” by two 3D agents using ...

This paper describes a pedagogical agent that helps children to learn to author structured presentations about explanations of concepts. Using a Rhetorical Structure Theory analysis of a source Web page, the agent performs pedagogical tasks to support the user's understanding of rhetorical relations, stimulates reflection about the relations between the structure of the original text and the st...

The Text2Dialogue (T2D) system that we are developing allows digital content creators to generate attractive multi-modal dialogues presented by two virtual agents—by simply providing textual information as input. We use Rhetorical Structure Theory (RST) to decompose text into segments and to identify rhetorical discourse relations between them. These are then “acted out” by two 3D agents using ...

This work aims to explore the correlation between the discourse structure of a spoken monologue and its prosody by predicting discourse relations from different prosodic attributes. For this purpose, a corpus of semi-spontaneous monologues in English has been automatically annotated according to the Rhetorical Structure Theory, which models coherence in text via rhetorical relations. From corre...

Overloaded and disinterested consumers have become skillful at screening out ads. In response, advertisers employ and combine various strategies, with two major ones being (a) rhetorical figures (e.g., rhyme, puns) and (b) message repetition. Though each has received substantial research attention and is crucial to advertising theory, they have not been examined simultaneously. We conducted a m...

This paper addresses semantic ellipsis control in language generation for humancomputer dialogue. For this, the rhetorical structure of the dialogue is used, as well as a repository of facts that are accepted by the recipient of the utterance. Rhetorical structure is represented in the framework of SDRT, where rhetorical relations are grouped in “confirmation” and “contradiction” relations; the...

In recent years, There has been a variety of research on discourse parsing, particularly RST discourse parsing (Feng and Hirst, 2014; Li et al., 2014b; Ji and Eisenstein, 2014; Joty and Moschitti, 2014; Li et al., 2014a). Most of the recent work on RST parsing has focused on implementing new types of features or learning algorithms in order to improve accuracy, with relatively little focus on e...