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Learning Transformation Rules for Semantic Role Labeling

This paper presents our work on Semantic Role Labeling using a Transformation-Based Error-Driven approach in the style of Eric Brill (Brill, 1995). Our approach achieved an overall F1 score of 43.48 on non-verb annotations. We believe our approach is noteworthy because of its novelty in this area and because it produces short lists of human-understandable transformation rules as its output.