  In this paper, we explore the application of Generative Pre-trained
Transformers (GPTs) in cross-lingual legal Question-Answering (QA) systems
using the COLIEE Task 4 dataset. In the COLIEE Task 4, given a statement and a
set of related legal articles that serve as context, the objective is to
determine whether the statement is legally valid, i.e., if it can be inferred
from the provided contextual articles or not, which is also known as an
entailment task. By benchmarking four different combinations of English and
Japanese prompts and data, we provide valuable insights into GPTs' performance
in multilingual legal QA scenarios, contributing to the development of more
efficient and accurate cross-lingual QA solutions in the legal domain.
