On the limited memory BFGS method for large scale optimization
Mathematical Programming: Series A and B
Blocking Gibbs sampling in very large probabilistic expert systems
International Journal of Human-Computer Studies - Special issue: real-world applications of uncertain reasoning
Unsupervised learning of name structure from coreference data
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Contrastive estimation: training log-linear models on unlabeled data
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Incorporating non-local information into information extraction systems by Gibbs sampling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Scalable training of L1-regularized log-linear models
Proceedings of the 24th international conference on Machine learning
Identification and tracing of ambiguous names: discriminative and generative approaches
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Joint unsupervised coreference resolution with Markov logic
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Structured generative models for unsupervised named-entity clustering
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Bayesian unsupervised word segmentation with nested Pitman-Yor language modeling
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
An entity-level approach to information extraction
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Large-scale cross-document coreference using distributed inference and hierarchical models
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
Structured databases of named entities from Bayesian nonparametrics
EMNLP '11 Proceedings of the First Workshop on Unsupervised Learning in NLP
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We present a statistical model for canonicalizing named entity mentions into a table whose rows represent entities and whose columns are attributes (or parts of attributes). The model is novel in that it incorporates entity context, surface features, first-order dependencies among attribute-parts, and a notion of noise. Transductive learning from a few seeds and a collection of mention tokens combines Bayesian inference and conditional estimation. We evaluate our model and its components on two datasets collected from political blogs and sports news, finding that it outperforms a simple agglomerative clustering approach and previous work.