Story Realization: Expanding Plot Events into Sentences
Table 4: Utilization percentages for each model combination on both events from the test set and from the full pipeline.
['[EMPTY]', '[BOLD] RetEdit Test', '[BOLD] RetEdit Pipeline', '[BOLD] Templates Test', '[BOLD] Templates Pipeline', '[BOLD] Monte Carlo Test', '[BOLD] Monte Carlo Pipeline', '[BOLD] FSM Test', '[BOLD] FSM Pipeline', '[BOLD] Seq2seq Test', '[BOLD] Seq2seq Pipeline']
Utilization percentages show us how often each model was picked in the respective ensembles based on the corresponding confidence score thresholds. RedEdit was heavily used on the test set, likely due the train and test sets having a similar distribution of data. On the pipeline events, RetEdit is used much less—events generated by event-to-event are often very different from those in the training set. A majority of the events that fall through RetEdit are caught by our Monte Carlo beam search, irrespective of the fact that RetEdit—and sentence templates—are most likely to honor the event tokens. This is partially due to the fact that satisfying the constraint of maintaining the events tokens makes it difficult for these models to meet the required threshold. The small portion of remaining events are transformed using the templates and the finite state machine.