Adaptive Transformation-Based Learning for Improving Dictionary Tagging.
Burcu Karagol-Ayan, David Doermann, Amy S. Weinberg · 2006
We present an adaptive technique that enables users to produce a high quality dictionary parsed into its lexicographic components (headwords, pronunciations, parts of speech, translations, etc.) using an extremely small amount of user provided training data. We use transformationbased learning (TBL) as a postprocessor at two points in our system to improve performance. The results using two dictionaries show that the tagging accuracy increases from 83 % and 91 % to 93 % and 94 % for individual words or “tokens”, and