Target Language Preposition Selection – an Experiment with Transformation-Based Learning and Aligned Bilingual Data

The translation of prepositions is often considered one of the more difficult tasks within the field of machine translation. We describe an experiment using transformationbased learning to induce rules to select the appropriate target language preposition from aligned bilingual data. Results show an accuracy of 84.9%, to be compared with a baseline of 75.5%, where the most frequent translation alternative is always chosen.