Automatically detecting discourse segments is an important preliminary step towards full discourse parsing. Previous research on discourse segmentation have relied on the assumption that elementary discourse units (EDUs) in a document always form a linear sequence (i.e., they can never be nested). Unfortunately, this assumption turns out to be too strong, for some theories of discourse like SDR...

Discourse relations in the recent literature are typically classified as either explicit (e.g., when a discourse connective like “because” is present) or implicit. This binary treatment of implicitness is advantageous for simplifying the explanation of many phenomena in discourse processing. On the other hand, linguists do not yet agree as to what types of textual particles contribute to reveal...

in this study, van dijk’s (1998) model of cda was utilized in order to examine the representation of iran’s nuclear program in editorials published by british news casting companies. the analysis of the editorials was carried out at two levels of headlines and full text stories with regard to the linguistic features of lexical choices, nominalization, passivization, overcompleteness, and voice....

Various NLP applications require automatic discourse analysis of texts. For analysis of scientific and technical texts, we propose to use all typical lexical units organizing scientific discourse; we call them common scientific words and expressions, most of them are known as discourse markers. The paper discusses features of scientific discourse, as well as the variety of discourse markers spe...

Nick Asher: (Invited): Constraints in Discourse: Part of a more general theory of rationality? SDRT promotes two central ideas relevant to constraints in discourse: (1) dynamic semantic update is constrained by discourse structure; (2) discourse coherence is a scalar phenomenon and so discourse structure construction should proceed by maximizing discourse coherence given the resources available...

The lack of annotated corpora brings limitations in research of discourse classification for many languages. In this paper, we present the first effort towards recognizing ambiguities of discourse connectives, which is fundamental to discourse classification for resource-poor language such as Chinese. A language independent framework is proposed utilizing bilingual dictionaries, Penn Discourse ...

Discourse Understanding is hard. This seems to be especially true for mathematical discourse, that is proofs. Restricting discourse to mathematical discourse allow us, however, to study the subject matter in its purest form. This domain of discourse is rich and welldefined, highly structured, offers a well-defined set of discourse relations and forces/allows us to apply mathematical reasoning. ...

The corpora available for training discourse relation classifiers are annotated using a general set of discourse relations. However, for certain applications, custom discourse relations are required. Creating a new annotated corpus with a new relation taxonomy is a timeconsuming and costly process. We address this problem by proposing a semi-supervised approach to discourse relation classificat...

I In this paper we present algorithms for the interpretation and generation of a kind of particu-larized conversational implicature occurring in certain indirect replies. Our algorithms make use of discourse expectations, discourse plans, and discourse relations. The algorithms calculate implica-tures of discourse units of one or more sentences. Our approach has several advantages. First, by ta...

Previous work by Lin et al. (2011) demonstrated the effectiveness of using discourse relations for evaluating text coherence. However, their work was based on discourse relations annotated in accordance with the Penn Discourse Treebank (PDTB) (Prasad et al., 2008), which encodes only very shallow discourse structures; therefore, they cannot capture long-distance discourse dependencies. In this ...