A transformation-based approach to argument labeling
Derrick Higgins · 2004
This paper presents the results of applying transformation-based learning (TBL) to the problem of semantic role labeling. The great advantage of the TBL paradigm is that it provides a simple learning framework in which the parallel tasks of argument identification and argument labeling can mutually influence one another. Semantic role