| Discussion | In the experiment described in Section 5, we used the linguistic information provided by human as the features on the maximum entropy method. |
| Experiment | Here, we used the maximum entropy method tool (Zhang, 2008) with the default options except “-i 2000.” |
| Linefeed Insertion Technique | These probabilities are estimated by the maximum entropy method. |
| Linefeed Insertion Technique | 4.2 Features on Maximum Entropy Method |
| Identification and Labeling Models | As in previous approaches to SRL, Brutus uses a two-stage pipeline of maximum entropy classifiers. |
| Introduction | For the identification and labeling steps, we train a maximum entropy classifier (Berger et al., 1996) over sections 02-21 of a version of the CCGbank corpus (Hockenmaier and Steedman, 2007) that has been augmented by projecting the Propbank semantic annotations (Boxwell and White, 2008). |
| Results | 6G&H use a generative model with a back-off lattice, whereas we use a maximum entropy classifier. |