Robust Processing of Natural Language
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TnT: a statistical part-of-speech tagger
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
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COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
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ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
Robust parsing using dynamic programming
CIAA'03 Proceedings of the 8th international conference on Implementation and application of automata
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EdAppsNLP '09 Proceedings of the Fourth Workshop on Innovative Use of NLP for Building Educational Applications
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This article describes an automatic evaluation procedure for NLP system robustness under the strain of noisy and ill-formed input. The procedure requires no manual work or annotated resources. It is language and annotation scheme independent and produces reliable estimates on the robustness of NLP systems. The only requirement is an estimate on the NLP system accuracy. The procedure was applied to five parsers and one part-of-speech tagger on Swedish text. To establish the reliability of the procedure, a comparative evaluation involving annotated resources was carried out on the tagger and three of the parsers.