Collective classification for fine-grained information status

Authors:
Katja Markert;Yufang Hou;Michael Strube
Affiliations:
University of Leeds, UK and Heidelberg Institute for Theoretical Studies gGmbH, Heidelberg, Germany;Heidelberg Institute for Theoretical Studies gGmbH, Heidelberg, Germany;Heidelberg Institute for Theoretical Studies gGmbH, Heidelberg, Germany
Venue:
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Year:
2012

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Abstract

Previous work on classifying information status (Nissim, 2006; Rahman and Ng, 2011) is restricted to coarse-grained classification and focuses on conversational dialogue. We here introduce the task of classifying fine-grained information status and work on written text. We add a fine-grained information status layer to the Wall Street Journal portion of the OntoNotes corpus. We claim that the information status of a mention depends not only on the mention itself but also on other mentions in the vicinity and solve the task by collectively classifying the information status of all mentions. Our approach strongly outperforms reimplementations of previous work.