Semantic role labelling with similarity-based generalization using em-based clustering
Ulrike Baldewein, Katrin Erk, Sebastian Padó, Detlef Prescher · 2004
We describe a system for semantic role assignment built as part of the Senseval III task, based on an off-the-shelf parser and Maxent and Memory-Based learners. We focus on generalisation using several similarity measures to increase the amount of training data available and on the use of EM-based clustering to improve role assignment. Our final score is Precision=73.6%, Recall=59.4 % (F=65.7). 1