Internal and external evidence in the identification and semantic categorization of proper names
Corpus processing for lexical acquisition
A maximum entropy approach to named entity recognition
A maximum entropy approach to named entity recognition
Nymble: a high-performance learning name-finder
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
MITRE: description of the Alembic system used for MUC-6
MUC6 '95 Proceedings of the 6th conference on Message understanding
Named entity recognition using an HMM-based chunk tagger
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Transformation-based learning in the fast lane
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Boosting trees for clause splitting
ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
Predicting accuracy of extracting information from unstructured text collections
Proceedings of the 14th ACM international conference on Information and knowledge management
Introduction to the CoNLL-2002 shared task: language-independent named entity recognition
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Named entity recognition through classifier combination
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Secure deletion from inverted indexes on compliance storage
Proceedings of the second ACM workshop on Storage security and survivability
Factorizing complex models: a case study in mention detection
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Combining data-driven systems for improving Named Entity Recognition
Data & Knowledge Engineering
Identifying semitic roots: Machine learning with linguistic constraints
Computational Linguistics
Named entity recognition for Ukrainian: a resource-light approach
ACL '07 Proceedings of the Workshop on Balto-Slavonic Natural Language Processing: Information Extraction and Enabling Technologies
Exploiting named entity taggers in a second language
ACLstudent '05 Proceedings of the ACL Student Research Workshop
Named entity recognition in tweets: an experimental study
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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This paper presents a classifier stacking-based approach to the named entity recognition task (NER henceforth). Transformation-based learning (Brill, 1995), Snow (sparse network of winnows (Muñoz et al., 1999)) and a forward-backward algorithm are stacked (the output of one classifier is passed as input to the next classifier), yielding considerable improvement in performance. In addition, in agreement with other studies on the same problem, the enhancement of the feature space (in the form of capitalization information) is shown to be especially beneficial to this task.