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This document discusses using reinforcement learning to improve information extraction when training data is limited. The proposed method retrieves external documents to resolve ambiguities in the original text. It formulates the problem as a reinforcement learning task to select optimal actions for querying additional documents and reconciling extracted values. The system is evaluated on datasets of shooting incidents and food adulterations, demonstrating improved accuracy over basic extractors and a meta-

Author

ry esg

Language

EN