A Hierarchical Model for Data-to-Text Generation
Table 1: Evaluation on the RotoWire testset using relation generation (RG) count (#) and precision (P%), content selection (CS) precision (P%) and recall (R%), content ordering (CO), and BLEU. -: number of parameters unavailable.
['[EMPTY]', 'BLEU', 'RG P%', 'RG #', 'CS P%', 'CS R%', 'CS F1', 'CO', 'Nb Params']
For each proposed variant of our architecture, we report the mean score over ten runs, as well as the standard deviation in subscript. We also report the result of the oracle (metrics on the gold descriptions). Please note that gold descriptions trivially obtain 100% on all metrics expect RG, as they are all based on comparison with themselves. RG scores are different, as the IE system is imperfect and fails to extract accurate entities 4% of the time. RG-# is an absolute count.