Abstract
We address the task of reference detection and classification in Czech court decisions. This task is a typical named-entity recognition task where the entities are references (links) to other documents.
We apply a supervised machine learning approach, namely Hidden Markov Models. A supervised methodology requires manual annotation of training data so we annotated 300 court decisions.