Automatic Prediction of Discourse Connectives
Table 2: Discourse connective prediction performance of a Random baseline, the WordPairs model, the decomposable attention model (DA) and human raters.
['Model', 'Macro F1', 'Accuracy']
In this section, the DA model and the WordPairs model are employed to perform the same task as the human raters, i.e., learning to reconstruct the connective possibly removed from the beginning of the second sentence in each test pair. The DA model is evaluated using the following hyper-parameters optimized on the development set: network size (one hidden layer with 200 neurons), batch size (64), dropout ratios for the F, G, and H networks (0.68, 0.14, and 0.44, respectively), and learning rate (0.0018).