Fig. 4. An example of combining ontology-based labeling functions.

Here four ontology labeling functions (MTH, CHV, LNC, SNOMEDCT) are used to label a sequence of words X_i containing the entity diabetes type 2. Majority vote estimates Y_i as a word-level sum of positive class labels, weighing each equally (a_MV). The label model learns a latent class-conditional accuracy (a_LM) for each ontology, which is used to reweight labels to generate a more accurate consensus prediction of Y_i.