Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Head-Driven Statistical Models for Natural Language Parsing
Computational Linguistics
Effective self-training for parsing
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Word-Level Confidence Estimation for Machine Translation
Computational Linguistics
Computer Assisted Transcription of Text Images and Multimodal Interaction
MLMI '08 Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction
Statistical approaches to computer-assisted translation
Computational Linguistics
Confidence Measures for Error Correction in Interactive Transcription Handwritten Text
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Interactive predictive parsing
IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
Balancing error and supervision effort in interactive-predictive handwriting recognition
Proceedings of the 15th international conference on Intelligent user interfaces
Interactive predictive parsing using a web-based architecture
HLT-DEMO '10 Proceedings of the NAACL HLT 2010 Demonstration Session
Products of random latent variable grammars
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Computer-assisted translation using speech recognition
IEEE Transactions on Audio, Speech, and Language Processing
Parsing of partially bracketed structures for parse selection
IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
| Hi-index | 0.00 |
We study the use of Confidence Measures (CM) for erroneous constituent discrimination in an Interactive Predictive Parsing (IPP) framework. The IPP framework allows to build interactive tree annotation systems that can help human correctors in constructing error-free parse trees with little effort (compared to manually post-editing the trees obtained from an automatic parser). We show that CMs can help in detecting erroneous constituents more quickly through all the IPP process. We present two methods for precalculating the confidence threshold (globally and per-interaction), and observe that CMs remain highly discriminant as the IPP process advances.