Class-based n-gram models of natural language
Computational Linguistics
The domain dependence of parsing
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
WordFreak: an open tool for linguistic annotation
NAACL-Demonstrations '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Demonstrations - Volume 4
Example selection for bootstrapping statistical parsers
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Reranking and self-training for parser adaptation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Self-training for biomedical parsing
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Adapting WSJ-trained parsers to the British National Corpus using in-domain self-training
IWPT '07 Proceedings of the 10th International Conference on Parsing Technologies
MAP adaptation of stochastic grammars
Computer Speech and Language
Improving generative statistical parsing with semi-supervised word clustering
IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
"cba to check the spelling" investigating parser performance on discussion forum posts
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Handling unknown words in statistical latent-variable parsing models for Arabic, English and French
SPMRL '10 Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages
SPMRL '10 Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages
DANLP 2010 Proceedings of the 2010 Workshop on Domain Adaptation for Natural Language Processing
Uptraining for accurate deterministic question parsing
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Benchmarking of statistical dependency parsers for French
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Learning domain differences automatically for dependency parsing adaptation
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
| Hi-index | 0.00 |
We present a simple and effective way to perform out-of-domain statistical parsing by drastically reducing lexical data sparseness in a PCFG-LA architecture. We replace terminal symbols with unsupervised word clusters acquired from a large newspaper corpus augmented with biomedical targetdomain data. The resulting clusters are effective in bridging the lexical gap between source-domain and target-domain vocabularies. Our experiments combine known self-training techniques with unsupervised word clustering and produce promising results, achieving an error reduction of 21% on a new evaluation set for biomedical text with manual bracketing annotations.