Data from: Evaluating active learning methods for annotating semantic predications

Jake Vasilakes, Rubina Rizvi, Genevieve B. Melton, Serguei Pakhomov & Rui Zhang
Objectives: This study evaluated and compared a variety of active learning strategies, including a novel strategy we proposed, as applied to the task of filtering incorrect SemRep semantic predications. Materials and Methods: We evaluated three types of active learning strategies – uncertainty, representative, and combined– on two datasets of semantic predications from SemMedDB covering the domains of substance interactions and clinical medicine, respectively. We also designed a novel combined strategy with dynamic β without hand-tuned...
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33 downloads reported since publication in 2019.

These counts follow the COUNTER Code of Practice, meaning that Internet robots and repeats within a certain time frame are excluded.
What does this mean?