Factuality Detection on the Cheap: Inferring Factuality for Increased Precision in Detecting Negated Events

This paper describes a system for discriminating between factual and non-factual contexts, trained on weakly labeled data by taking advantage of information implicit in annotations of negated events. In addition to evaluating factuality detection in isolation, we also evaluate its impact on a system for event detection. The two components for factuality detection and event detection form part of a system for identifying negative factual events, or counterfacts, with top-ranked results in the *SEM 2012 shared task.

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