Data-to-text Generation with Entity Modeling
Table 3: Ablation results on RotoWire (RW) and MLB development set using relation generation (RG) count and precision, content selection (CS) precision and recall, content ordering (CO) in normalized Damerau-Levenshtein distance, and BLEU.
['RW', 'RG', 'RG', 'CS', 'CS', 'CO', 'BLEU']
We compare ED+CC against variants “+Hier”, “+Dyn” and “+Gate” corresponding to successively adding hierarchical attention, dynamic memory, and the update gate mechanism. On both datasets, hierarchical attention, improves relation generation, content selection, and BLEU. Dynamic memory and the update gate brings further improvements to content selection and BLEU.