Large Margin Classification Using the Perceptron Algorithm
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
A machine learning approach to coreference resolution of noun phrases
Computational Linguistics - Special issue on computational anaphora resolution
Unrestricted Coreference: Identifying Entities and Events in OntoNotes
ICSC '07 Proceedings of the International Conference on Semantic Computing
Conundrums in noun phrase coreference resolution: making sense of the state-of-the-art
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Coreference resolution with reconcile
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
CoNLL-2011 shared task: modeling unrestricted coreference in OntoNotes
CONLL Shared Task '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning: Shared Task
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This paper describes our entry to the 2011 CoNLL closed task (Pradhan et al., 2011) on modeling unrestricted coreference in OntoNotes. Our system is based on the Reconcile coreference resolution research platform. Reconcile is a general software infrastructure for the development of learning-based noun phrase (NP) coreference resolution systems. Our entry for the CoNLL closed task is a configuration of Reconcile intended to do well on OntoNotes data. This paper describes our configuration of Reconcile as well as the changes that we had to implement to integrate with the OntoNotes task definition and data formats. We also present and discuss the performance of our system under different testing conditions on a withheld validation set.