Paragraph-by-paragraph machine translation seems to be for now, an unjustifiably complicated task for practical needs. It involves the complete understanding of the paragraph, the determination of discourse topic(s), goals, intentions, so that the output can be produced in accordance with the respective discourse rules and purposes. However, recognizing topic, goal, intention by a computer prog...

Paragraph-by-paragraph machine translation seems to be for now, an unjustifiably complicated task for practical needs. It involves the complete understanding of the paragraph, the determination of discourse topic(s), goals, intentions, so that the output can be produced in accordance with the respective discourse rules and purposes. However, recognizing topic, goal, intention by a computer prog...

In this paper we describe Danish and Italian parallel and comparable texts annotated with (co)referential chains and information about discourse topic shifts, and present an evaluation of the annotation. We also discuss general differences in the way referring expressions are used in Danish and Italian and present the analysis of the relation between the use of types of referring expression and...

Discourse markers are words or phrases that function as indicators of the structure of discourse by e.g. signalling the beginning of a new topic. This study reports on the Swedish discourse markers men ‘but’/‘and’ and så ‘so’, their functions and prosodic correlates in dialogue.

Centering theory posits a discourse center, a distinguished discourse entity that is the topic of a discourse. A simplified version of this theory is developed in a Dynamic Semantics framework. In the resulting system, the mechanism of center shift allows a simple, elegant analysis of a variety of phenomena involving sloppy identity in ellipsis and “paycheck pronouns”.

We present a novel Bayesian topic model for learning discourse-level document structure. Our model leverages insights from discourse theory to constrain latent topic assignments in a way that reflects the underlying organization of document topics. We propose a global model in which both topic selection and ordering are biased to be similar across a collection of related documents. We show that...

We present a novel Bayesian topic model for learning discourse-level document structure. Our model leverages insights from discourse theory to constrain latent topic assignments in a way that reflects the underlying organization of document topics. We propose a global model in which both topic selection and ordering are biased to be similar across a collection of related documents. We show that...

We present a novel Bayesian topic model for learning discourse-level document structure. Our model leverages insights from discourse theory to constrain latent topic assignments in a way that reflects the underlying organization of document topics. We propose a global model in which both topic selection and ordering are biased to be similar across a collection of related documents. We show that...

Nowadays discourse parsing is a very prominent research topic. However, there is not a discourse parser for Spanish texts. The first stage in order to develop this tool is discourse segmentation. In this work, we present DiSeg, the first discourse segmenter for Spanish that uses the framework of the Rhetorical Structure Theory (Mann and Thompson, 1988) and is based on lexical and syntactic rule...