The calibrated confidence output by the sigmoid layer of our hashtag disambiguation model can be regarded as a measurement of the reliability of an instance (Niculescu-Mizil and Caruana, 2005;Guo et al., 2017).
we can sort all self-labeled data by their calibrated confidence and control the size of training set by adjusting the threshold.