WordNet: a lexical database for English
Communications of the ACM
A maximum entropy approach to natural language processing
Computational Linguistics
A machine learning approach to coreference resolution of noun phrases
Computational Linguistics - Special issue on computational anaphora resolution
A model-theoretic coreference scoring scheme
MUC6 '95 Proceedings of the 6th conference on Message understanding
On coreference resolution performance metrics
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
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
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
Blanc: Implementing the rand index for coreference evaluation
Natural Language Engineering
Coreference resolution using tree CRFs
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
CoNLL-2012 shared task: Modeling Multilingual Unrestricted Coreference in OntoNotes
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
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Coreference resolution, which aims at correctly linking meaningful expressions in text, is a much challenging problem in Natural Language Processing community. This paper describes the multilingual coreference modeling system of Web Information Processing Group, Henan University of Technology, China, for the CoNLL-2012 shared task (closed track). The system takes a supervised learning strategy, and consists of two cascaded components: one for detecting mentions, and the other for clustering mentions. To make the system applicable for multiple languages, generic syntactic and semantic features are used to model coreference in text. The system obtained combined official score 41.88 over three languages (Arabic, Chinese, and English) and ranked 7th among the 15 systems in the closed track.