It is important that NLP applications such as named entity recognition and question answering produce calibrated confidence scores for their predictions, especially if the applications are to be deployed in a safetycritical domain such as healthcare.
the output space of such structured prediction models is often too large to adapt binary or multi-class calibration methods directly.