An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Discourse and Information Structure
Journal of Logic, Language and Information
A corpus-based investigation of definite description use
Computational Linguistics
Corpus-based identification of non-anaphoric noun phrases
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Identifying anaphoric and non-anaphoric noun phrases to improve coreference resolution
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
High-precision identification of discourse new and unique noun phrases
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 2
Automatically learning cognitive status for multi-document summarization of newswire
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Learning information status of discourse entities
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Incorporating information status into generation ranking
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 2 - Volume 2
Identifying generic noun phrases
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Practical very large scale CRFs
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Language Resources and Evaluation
Learning noun phrase anaphoricity in coreference resolution via label propagation
Journal of Computer Science and Technology - Special issue on natural language processing
Learning the information status of noun phrases in spoken dialogues
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Learning the fine-grained information status of discourse entities
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
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We present a model for automatically predicting information status labels for German referring expressions. We train a CRF on manually annotated phrases, and predict a fine-grained set of labels. We achieve an accuracy score of 69.56% on our most detailed label set, 76.62% when gold standard coreference is available.