1. A computer-implemented method, comprising: obtaining a first quality model that was trained using a first set of training entities; identifying a set of candidate entities, where each candidate entity is different from each of the training entities; for each candidate entity in the set of candidate entities: obtaining a first quality score for the candidate entity; obtaining one or more neighbor features for neighbor entities of the candidate entity, where each neighbor entity of the candidate entity is an entity that is linked to the candidate entity; obtaining one or more entity specific feature values for the candidate entity, where each entity specific feature value is determined independent of the neighbor entities of the candidate entity; and determining a second quality score for the candidate entity using the first quality model, the second quality score being computed based on the first quality score, the neighbor features, and the entity specific feature values.