Latent structure perceptron with feature induction for unrestricted coreference resolution
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
Data-driven multilingual coreference resolution using resolver stacking
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
Combining the best of two worlds: a hybrid approach to multilingual coreference resolution
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
Using syntactic dependencies to solve coreferences
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
ICT: system description for CoNLL-2012
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
A mixed deterministic model for coreference resolution
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
Simple maximum entropy models for multilingual coreference resolution
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
UBIU for multilingual coreference resolution in OntoNotes
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
A multigraph model for coreference resolution
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
Incorporating rule-based and statistic-based techniques for coreference resolution
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
Illinois-Coref: the UI system in the CoNLL-2012 shared task
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
Hybrid rule-based algorithm for coreference resolution
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
BART goes multilingual: the UniTN/Essex submission to the CoNLL-2012 shared task
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
Learning to model multilingual unrestricted coreference in OntoNotes
CoNLL '12 Joint Conference on EMNLP and CoNLL - Shared Task
End-to-end coreference resolution for clinical narratives
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
A constraint-based hypergraph partitioning approach to coreference resolution
Computational Linguistics
Deterministic coreference resolution based on entity-centric, precision-ranked rules
Computational Linguistics
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The CoNLL-2012 shared task involved predicting coreference in three languages -- English, Chinese and Arabic -- using OntoNotes data. It was a follow-on to the English-only task organized in 2011. Until the creation of the OntoNotes corpus, resources in this subfield of language processing have tended to be limited to noun phrase coreference, often on a restricted set of entities, such as ACE entities. OntoNotes provides a large-scale corpus of general anaphoric coreference not restricted to noun phrases or to a specified set of entity types and covering multiple languages. OntoNotes also provides additional layers of integrated annotation, capturing additional shallow semantic structure. This paper briefly describes the OntoNotes annotation (coreference and other layers) and then describes the parameters of the shared task including the format, pre-processing information, evaluation criteria, and presents and discusses the results achieved by the participating systems. Being a task that has a complex evaluation history, and multiple evalation conditions, it has, in the past, been difficult to judge the improvement in new algorithms over previously reported results. Having a standard test set and evaluation parameters, all based on a resource that provides multiple integrated annotation layers (parses, semantic roles, word senses, named entities and coreference) that could support joint models, should help to energize ongoing research in the task of entity and event coreference.