Children can learn new words from non-instructive contexts (e.g., overheard speech). Recently, it has been proposed that one way that children do this is by using the surrounding discourse to constrain the interpretation of new words (Sullivan & Barner, 2015). However, little is known about what sort of discourse inferences children might compute when learning. In the present study, we adopt a ...

AIM The aim of the paper is (1) to offer an overview of different theoretical approaches to discourse analysis and (2) to review papers published in the Journal of Advanced Nursing from 1996-2004 in which discourse analysis is identified as a method of data analysis. BACKGROUND Discourse analysis offers rigorous approaches to analysing naturally occurring talk and texts. Forms of discourse an...

While it seems intuitively obvious tha t many discourse markers (DMs) are able to express discourse relat ions (DRs) which ex i s t independently, the specific contr ibut ion of DMs if any is not clear. In this paper , we investigate the s tatus of some consequence DMs in French. We observe tha t it is difficult to cons t ruc t a clear and simple definition based on DRs for these DMs. Next , we...

Discourse parsing is a challenging task in NLP and plays a crucial role in discourse analysis. To enable discourse analysis for Hindi, Hindi Discourse Relations Bank was created on a subset of Hindi TreeBank. The benefits of a discourse analyzer in automated discourse analysis, question summarization and question answering domains has motivated us to begin work on a discourse analyzer for Hindi...

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 ...