Generalized Grounding Graphs: A Probabilistic Framework for Understanding Grounded Commands
Table 2: Performance of the learned model at predicting the correspondence variable ϕ.
['Constituent type', 'Precision', 'Recall', 'F-score', 'Accuracy']
The performance of the model on this corpus indicates that it robustly learns to predict when constituents match groundings from the corpus. We evaluated how much training was required to achieve good performance on the test dataset and found that the test error asymptotes at around 1,000 (of 3,000) annotated constituents.