COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Active Learning for Natural Language Parsing and Information Extraction
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Employing EM and Pool-Based Active Learning for Text Classification
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
The reliability of a dialogue structure coding scheme
Computational Linguistics
Rule writing or annotation: cost-efficient resource usage for base noun phrase chunking
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
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 with character-level models
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Multilingual resources for entity extraction
MultiNER '03 Proceedings of the ACL 2003 workshop on Multilingual and mixed-language named entity recognition - Volume 15
Introduction to the bio-entity recognition task at JNLPBA
JNLPBA '04 Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications
A stopping criterion for active learning
Computer Speech and Language
On proper unit selection in active learning: co-selection effects for named entity recognition
HLT '09 Proceedings of the NAACL HLT 2009 Workshop on Active Learning for Natural Language Processing
Evaluating automation strategies in language documentation
HLT '09 Proceedings of the NAACL HLT 2009 Workshop on Active Learning for Natural Language Processing
An empirical approach to the interpretation of superlatives
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Tools to address the interdependence between tokenisation and standoff annotation
NLPXML '06 Proceedings of the 5th Workshop on NLP and XML: Multi-Dimensional Markup in Natural Language Processing
Efficient annotation with the Jena ANnotation Environment (JANE)
LAW '07 Proceedings of the Linguistic Annotation Workshop
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Bucking the trend: large-scale cost-focused active learning for statistical machine translation
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
A cognitive cost model of annotations based on eye-tracking data
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
A comparison of models for cost-sensitive active learning
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Active learning with Amazon Mechanical Turk
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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We report on an active learning experiment for named entity recognition in the astronomy domain. Active learning has been shown to reduce the amount of labelled data required to train a supervised learner by selectively sampling more informative data points for human annotation. We inspect double annotation data from the same domain and quantify potential problems concerning annotators' performance. For data selectively sampled according to different selection metrics, we find lower inter-annotator agreement and higher per token annotation times. However, overall results confirm the utility of active learning.