The PhotoBook Dataset:Building Common Ground through Visually-Grounded Dialogue
Table 2: Number of reference chains, dialogue segments, and image types (targets and non-targets) in each data split.
['[BOLD] Split', '[BOLD] Chains', '[BOLD] Segments', '[BOLD] Targets', '[BOLD] Non-Targets']
The automatically extracted co-reference chains per target image were split into three disjoint sets for training (70%), validation (15%) and testing (15%), aiming at an equal distribution of target image domains in all three sets. The results show that the resolution capabilities of our model are well above the baseline. The History model achieves higher recall and F-score than the No-History model, while precision is comparable across these two conditions.