Adaptive Transformation-based Learning for Improving Dictionary Tagging

TitleAdaptive Transformation-based Learning for Improving Dictionary Tagging
Publication TypeConference Papers
Year of Publication2006
AuthorsKaragol-Ayan B, Doermann D, Weinberg A
Conference NameProceedings of the 11th Conference on European Chapter of the Association for Computational Linguistics
Date Published2006/04//
Conference LocationTrento, Italy

We present an adaptive technique that enables users to produce a high quality dictionary parsed into its lexicographic components (headwords, parts of speech, translations, etc.) using an extremely small amount of user provided training data. We use transformation-based learning (TBL) as a postprocessor at two points in the system to improve performance. The results show that the tagging accuracy is increased from 83% and 91% to 93% and 94% for individual words or tokens , and from 64% and 83% to 90% and 93% for contiguous phrases such as definitions or examples of usage.