Functional arguments detection using decision trees
Abstract
This paper shows how decision trees can help addressing the problem of functional arguments detection, namely logical subjects. On a set of 14 target-verbs widely used in verb studies, verb-centered models provide almost similar results with all-verbs models. When traces in training data are solved the size of training increases with about 10% while the performance remains the same with the advantage of a more reliable estimation.
Publication Title
Proceedings of the International Conference on Artificial Intelligence, IC-AI'04
Recommended Citation
Rus, V. (2004). Functional arguments detection using decision trees. Proceedings of the International Conference on Artificial Intelligence, IC-AI'04, 1, 275-280. Retrieved from https://digitalcommons.memphis.edu/facpubs/2842
