Latent Relation Language Models
Table 6: Perplexity values of models on WikiFacts, lower is better. “+ Entity” means trained with extra entities; “+ Oracle char model” means treating the character model as oracle, i.e., treating spell-out probabilities of OOV words as 1. Best results are in bold. Note that our results are not directly comparable with reported results by Ahn et al. (2016) due to different dataset splits being used.
['Dataset', 'Dev Vanilla LM', 'Dev NKLM', 'Dev LRLM', 'Test Vanilla LM', 'Test NKLM', 'Test LRLM']
The inclusion of extra entities significantly improves results for both models. This is due to the fact that these entities are extracted from hyperlinks within text, so 1) they are mostly rare words; 2) the model can easily learn that all such entities must be included in the text at some point.