The recognition of the named entity in the judgment documents is the key step in the automatic trial. How to effectively distinguish the key named entity of the case is the key point in this study. Therefore, this study proposes a neural network model based on SVM-BiLSTM-CRF for property dispute of trial cases. First, the sentences containing the key named entities are selected by SVM, and then the sentences are converted into the character level vectors as input, and the BiLSTM-CRF deep neural network model suitable for the identification of the property dispute referee's named entity is constructed. By constructing training data for verification and comparison, the model shows higher recall and accuracy than other related models.