What Happened? Leveraging VerbNet to Predict the Effects of Actions in Procedural Text
Table 2: Results for ProComp and two recent RC systems (ProRead and BiDAF) on the OldProPara data (test set). Scores are macroaveraged, F1 differences are statistically significant (p<0.05).
['[EMPTY]', 'Single Answer Questions', 'Single Answer Questions', 'Single Answer Questions', 'All Questions', 'All Questions', 'All Questions']
ProComp significantly outperforms the baselines on both the full test set, and the single answer questions subset (removing ProRead and BiDAF ’s disadvantage of producing just one answer). ProComp also significantly outperforms BiDAF, but by a smaller amount. We analyze the respective stengths and weaknesses of ProComp and BiDAF in detail in the Analysis Section. Similar differences hold on All Qns.