Year: 2008
Type: conference-paper
Abstract: Research on coreference resolution and summarization has modeled the way entities are realized as concrete phrases in discourse. In particular there exist models of the noun phrase syntax used for discourse-new versus discourse-old referents, and models describing the likely distance between a pronoun and its antecedent. However, models of discourse coherence, as applied to information ordering tasks, have ignored these kinds of information. We apply a discourse-new classifier and pronoun coreference algorithm to the information ordering task, and show significant improvements in performance over the entity grid, a popular model of local coherence.
Authors: Micha Elsner, Eugene Charniak
Institution: Brown University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W2159757335