Improving Neural Relation Extraction with Positive and Unlabeled Learning
Table 1: Manual evaluation results
['Accuracy', 'Top 100', 'Top 200', 'Top 500']
Due to existence of noises resulting from distant supervision and the incomplete nature of Freebase, a majority of the tuples that were produced with high confidence are false negatives and are actually true relation instances.