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
Coreference resolution in a modular, entity-centered model
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
A multi-pass sieve for coreference resolution
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Bootstrapping coreference resolution using word associations
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Stanford's multi-pass sieve coreference resolution system at the CoNLL-2011 shared task
CONLL Shared Task '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning: Shared Task
Inference protocols for coreference resolution
CONLL Shared Task '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning: Shared Task
Exploring lexicalized features for coreference resolution
CONLL Shared Task '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning: Shared Task
CoNLL-2012 shared task: Modeling Multilingual Unrestricted Coreference in OntoNotes
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
Deterministic coreference resolution based on entity-centric, precision-ranked rules
Computational Linguistics
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This paper describes our coreference resolution system for the CoNLL-2012 shared task. Our system is based on the Stanford's dcoref deterministic system which applies multiple sieves with the order from high precision to low precision to generate coreference chains. We introduce the newly added constraints and sieves and discuss the improvement on the original system. We evaluate the system using OntoNotes data set and report our results of average F-score 58.25 in the closed track.