Abstract
Information extraction, and specifically event and relation extraction from text, is an important problem in the age of big data. Current solutions to these problems require large amounts of training data or extensive feature engineering to find domain-specific events. We introduce a novel Interactive Learning approach that greatly reduces the number of training examples needed and requires no feature engineering. Our method achieves event detection precision in the 80 s and 90 s with only 1 h of human supervision.
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