Recent advances in data-to-text generation have led to the use of large-scale datasets and
neural network models which are trained end-to-end, without explicitly modeling what to say …

This article proposes a novel framework for representing and measuring local coherence.
Central to this approach is the entity-grid representation of discourse, which captures …

The ability to convey relevant and faithful information is critical for many tasks in conditional
generation and yet remains elusive for neural seq-to-seq models whose outputs often reveal …

Centering theory is the best-known framework for theorizing about local coherence and
salience; however, its claims are articulated in terms of notions which are only partially …

This article considers the automatic evaluation of information ordering, a task underlying
many text-based applications such as concept-to-text generation and multidocument …

Automatic story comprehension is a fundamental challenge in Natural Language
Understanding, and can enable computers to learn about social norms, human behavior …

In the five years since it was proposed, the MATE scheme for anaphoric annotation has
been used in a variety of annotation projects, and the resulting corpora have been used to …

Discourse Annotation and Semantic Annotation in the GNOME Corpus Page 1 Discourse
Annotation and Semantic Annotation in the GNOME Corpus Massimo Poesio University of …

In a language generation system, a content planner selects which elements must be
included in the output text and the ordering between them. Recent empirical approaches …

We present the first algorithm that computes optimal orderings of sentences into a locally
coherent discourse. The algorithm runs very efficiently on a variety of coherence measures …