Coreference Resolution
Overview
Coreference resolution is the task of finding all expressions that refer to the same entity in a text. It is an important step for a lot of higher level NLP tasks that involve natural language understanding such as document summarization, question answering, and information extraction.
People
Software
A java implementation of our coreference resolution system is available online.
Publications
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Kevin Clark
and Christopher Manning.
2016.
Deep Reinforcement Learning for Mention-Ranking Coreference Models.
In Proceedings of EMNLP 2016.
[pdf,
bib]
-
Kevin Clark
and Christopher Manning.
2016.
Improving Coreference Resolution by Learning Entity-Level Distributed Representations.
In Proceedings of ACL 2016.
[pdf,
bib]
-
Kevin Clark
and Christopher Manning.
2015.
Entity-Centric Coreference Resolution with Model Stacking.
In Proceedings of ACL 2015.
[pdf,
bib]
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Marta Recasens,
Matthew Can,
and Dan Jurafsky.
2013.
Same Referent, Different Words: Unsupervised Mining of Opaque Coreferent Mentions.
In Proceedings of NAACL 2013.
[pdf,
bib;
data]
-
Marta Recasens,
Marie-Catherine de Marneffe,
and Christopher Potts.
2013.
The Life and Death of Discourse Entities: Identifying Singleton Mentions.
In Proceedings of NAACL 2013.
[pdf,
bib;
best short paper award]
-
Heeyoung Lee,
Marta Recasens,
Angel Chang,
Mihai Surdeanu,
and Dan Jurafsky.
2012.
Joint Entity and Event Coreference Resolution across Documents.
In Proceedings of the
Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
(EMNLP-CoNLL).
[pdf,
bib]
-
Heeyoung Lee, Yves Peirsman, Angel Chang, Nathanael Chambers, Mihai Surdeanu, Dan Jurafsky.
Stanford's Multi-Pass Sieve Coreference Resolution System at the CoNLL-2011 Shared Task.
In Proceedings of the CoNLL-2011 Shared Task, 2011.
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Karthik Raghunathan, Heeyoung Lee, Sudarshan Rangarajan, Nathanael Chambers, Mihai Surdeanu, Dan Jurafsky, Christopher Manning. 2010.
A Multi-Pass Sieve for Coreference Resolution
EMNLP-2010, Boston, USA. 2010.
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