Since there may be many sentences containing a given entity pair, we can extract very large numbers of (potentially noisy) features that are combined in a logistic regression classifier.
whereas the supervised training paradigm uses a small labeled corpus of only 17,000 relation instances as training data, our algorithm can use much larger amounts of data: more text, more relations, and more instances.