A sequence labelling approach to quote attribution

Authors:
Tim O'Keefe;Silvia Pareti;James R. Curran;Irena Koprinska;Matthew Honnibal
Affiliations:
University of Sydney, NSW, Australia;University of Edinburgh, United Kingdom;University of Sydney, NSW, Australia;University of Sydney, NSW, Australia;Macquarie University, NSW, Australia
Venue:
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Year:
2012

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Abstract

Quote extraction and attribution is the task of automatically extracting quotes from text and attributing each quote to its correct speaker. The present state-of-the-art system uses gold standard information from previous decisions in its features, which, when removed, results in a large drop in performance. We treat the problem as a sequence labelling task, which allows us to incorporate sequence features without using gold standard information. We present results on two new corpora and an augmented version of a third, achieving a new state-of-the-art for systems using only realistic features.