We compared our full model with gold texts, template-based system, CC <cite>(Wiseman et al., 2017)</cite> and NCP+CC (NCP) (Puduppully et al., 2019) . We randomly sampled 30 examples from test set. Then, we randomly sampled 4 sentences from each model's output for each example. We provided the raters of those sampled sentences with the corresponding NBA game statistics. They were asked to count the number of supporting and contradicting facts in each sentence. Each sentence is rated independently. We report the average number of supporting facts (#Sup) and contradicting facts (#Cont) in Table 3 . Unsurprisingly, template-based system includes most supporting facts and least contradicting facts in its texts because the template consists of a large number of facts and all of those facts are extracted from the table. Also, our model produces less contradicting facts than other two neural models.