Evaluating centering for information ordering using corpora

Nikiforos Karamanis, Chris Mellish, Massimo Poesio, Jon Oberlander

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)
10 Downloads (Pure)

Abstract

In this article we discuss several metrics of coherence defined using centering theory and investigate the usefulness of such metrics for information ordering in automatic text generation. We estimate empirically which is the most promising metric and how useful this metric is using a general methodology applied on several corpora. Our main result is that the simplest metric (which relies exclusively on NOCB transitions) sets a robust baseline that cannot be outperformed by other metrics which make use of additional centering-based features. This baseline can be used for the development of both text-to-text and concept-to-text generation systems.
Original languageEnglish
Pages (from-to)29-46
Number of pages18
JournalComputational Linguistics
Volume35
Issue number1
DOIs
Publication statusPublished - Mar 2009

Bibliographical note

Many thanks to Aggeliki Dimitromanolaki, Mirella Lapata, and Regina Barzilay for their data; to David Schlangen, Ruli Manurung, James Soutter, and Le An Ha for programming solutions; and to Ruth Seal and two anonymous reviewers for their
comments. Nikiforos Karamanis received support from the Greek State Scholarships Foundation (IKY) as a PhD student in Edinburgh as well as the Rapid Item
Generation project and the BBSRC-funded FlySlip grant (No 38688) as a postdoc in
Wolverhampton and Cambridge, respectively

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