Textual Analogy Parsing: What’s Shared and What’s Compared among Analogous Facts
Table 3: Performance of models on the test data. Combining the neural model with linguistic features and using an optimal decoder to enforce semantic constraints led to the best performance.
['Model', 'Feats.', 'Dec.', 'Frame prediction P', 'Frame prediction R', 'Frame prediction  [ITALIC] F1']
Our three main findings are that (i) the neural network model far outperforms the log-linear model on our frame metric, (ii) including linguistic features further increases performance, and (iii) so does using an optimal decoder over a greedy method.