Arabic cross-document coreference detection

Authors:
Asad Sayeed;Tamer Elsayed;Nikesh Garera;David Alexander;Tan Xu;Douglas W. Oard;David Yarowsky;Christine Piatko
Affiliations:
Johns Hopkins University, Baltimore, MD and University of Maryland, College Park, MD;Johns Hopkins University, Baltimore, MD and University of Maryland, College Park, MD;Johns Hopkins University, Baltimore, MD;Johns Hopkins University, Baltimore, MD and BBN Technologies, Cambridge, MA;Johns Hopkins University, Baltimore, MD and University of Maryland, College Park, MD;Johns Hopkins University, Baltimore, MD and University of Maryland, College Park, MD;Johns Hopkins University, Baltimore, MD;Johns Hopkins University, Baltimore, MD
Venue:
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
Year:
2009

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Abstract

We describe a set of techniques for Arabic cross-document coreference resolution. We compare a baseline system of exact mention string-matching to ones that include local mention context information as well as information from an existing machine translation system. It turns out that the machine translation-based technique outperforms the baseline, but local entity context similarity does not. This helps to point the way for future cross-document coreference work in languages with few existing resources for the task.