Legal Entity Recognition in Indonesian Court Decision Documents Using Bi-LSTM and CRF Approaches

The increasing number of Indonesian court decision documents requires special attention to be managed and used efficiently. One thing is to recognize legal entities to identify relevant legal information in the documents. This research examines the effectiveness of several deep learning methods, to recognize ten legal entities in Indonesian court decision documents. In this task, we found that the combination of Bi-LSTM and CRF methods achieve the highest F-1 score of 0.83. It outperforms other deep learning methods (CNN, LSTM, LSTM+CRF and Bi-LSTM) by 2 - 12 % and machine learning methods (SVM and CRF) by 41 - 76 %. The results show that this model can be used to identify relevant information about the legal domain in Indonesia.