Improving Distant Supervision for Information Extraction Using Label Propagation Through Lists

Because of polysemy, distant labeling for information extraction leads to noisy training data. We describe a procedure for reducing this noise by using label propagation on a graph in which the nodes are entity mentions, and mentions are coupled when they occur in coordinate list structures. We show that this labeling approach leads to good performance even… CONTINUE READING

7 Figures & Tables

Statistics

051015201620172018
Citations per Year

Citation Velocity: 8

Averaging 8 citations per year over the last 3 years.

Learn more about how we calculate this metric in our FAQ.