TY - GEN
T1 - Adapting coreference resolution for narrative processing
AU - Do, Quynh Ngoc Thi
AU - Bethard, Steven
AU - Moens, Marie Francine
N1 - Publisher Copyright:
© 2015 Association for Computational Linguistics.
PY - 2015
Y1 - 2015
N2 - Domain adaptation is a challenge for supervised NLP systems because of expensive and time-consuming manual annotated resources. We present a novel method to adapt a supervised coreference resolution system trained on newswire to short narrative stories without retraining the system. The idea is to perform inference via an Integer Linear Programming (ILP) formulation with the features of narratives adopted as soft constraints. When testing on the UMIREC1 and N22 corpora with the-stateof-the-art Berkeley coreference resolution system trained on OntoNotes3, our inference substantially outperforms the original inference on the CoNLL 2011 metric.
AB - Domain adaptation is a challenge for supervised NLP systems because of expensive and time-consuming manual annotated resources. We present a novel method to adapt a supervised coreference resolution system trained on newswire to short narrative stories without retraining the system. The idea is to perform inference via an Integer Linear Programming (ILP) formulation with the features of narratives adopted as soft constraints. When testing on the UMIREC1 and N22 corpora with the-stateof-the-art Berkeley coreference resolution system trained on OntoNotes3, our inference substantially outperforms the original inference on the CoNLL 2011 metric.
UR - http://www.scopus.com/inward/record.url?scp=84959887520&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84959887520&partnerID=8YFLogxK
U2 - 10.18653/v1/d15-1271
DO - 10.18653/v1/d15-1271
M3 - Conference contribution
AN - SCOPUS:84959887520
T3 - Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing
SP - 2262
EP - 2267
BT - Conference Proceedings - EMNLP 2015
PB - Association for Computational Linguistics (ACL)
T2 - Conference on Empirical Methods in Natural Language Processing, EMNLP 2015
Y2 - 17 September 2015 through 21 September 2015
ER -