  The Competition on Legal Information Extraction/Entailment (COLIEE) is held
annually to encourage advancements in the automatic processing of legal texts.
Processing legal documents is challenging due to the intricate structure and
meaning of legal language. In this paper, we outline our strategies for
tackling Task 2, Task 3, and Task 4 in the COLIEE 2023 competition. Our
approach involved utilizing appropriate state-of-the-art deep learning methods,
designing methods based on domain characteristics observation, and applying
meticulous engineering practices and methodologies to the competition. As a
result, our performance in these tasks has been outstanding, with first places
in Task 2 and Task 3, and promising results in Task 4. Our source code is
available at https://github.com/Nguyen2015/CAPTAIN-COLIEE2023/tree/coliee2023.
