Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
MUC4 '92 Proceedings of the 4th conference on Message understanding
GE NLToolset: MUC-4 test results and analysis
MUC4 '92 Proceedings of the 4th conference on Message understanding
HLT '91 Proceedings of the workshop on Speech and Natural Language
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Cascading use of soft and hard matching pattern rules for weakly supervised information extraction
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Structure compilation: trading structure for features
Proceedings of the 25th international conference on Machine learning
Generalized expectation criteria for bootstrapping extractors using record-text alignment
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
A unified model of phrasal and sentential evidence for information extraction
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
On dual decomposition and linear programming relaxations for natural language processing
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Collective cross-document relation extraction without labelled data
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Dual decomposition for parsing with non-projective head automata
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
In-domain relation discovery with meta-constraints via posterior regularization
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Template-based information extraction without the templates
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Fast and robust joint models for biomedical event extraction
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
| Hi-index | 0.00 |
This paper addresses the extraction of event records from documents that describe multiple events. Specifically, we aim to identify the fields of information contained in a document and aggregate together those fields that describe the same event. To exploit the inherent connections between field extraction and event identification, we propose to model them jointly. Our model is novel in that it integrates information from separate sequential models, using global potentials that encourage the extracted event records to have desired properties. While the model contains high-order potentials, efficient approximate inference can be performed with dual-decomposition. We experiment with two data sets that consist of newspaper articles describing multiple terrorism events, and show that our model substantially outperforms traditional pipeline models.