Everything Happens for a Reason: Discovering the Purpose of Actions in Procedural Text
Table 2: Effect of ablating gedge and gkb from XPAD (test set).
['Ablation', 'Dependency Task P', 'Dependency Task R', 'Dependency Task F1']
Removing gkb, results in a substantial (9 points) drop in recall, since the action dependency priors uses background knowledge to help the model discover dependency links that the model could not infer from the current paragraph. Further, removing gedge score results in around 2 points drop in recall and a substantial increase in precision (F1 is still lower). This is because the gedge score encourages the model to predict state changes that result in more action dependency links, often at the cost of a drop in precision. Thus, the gedge and gkb scores together help XPAD discover meaningful action dependency links.