This paper describes the NOWJ1 Team's approach for the Automated Legal
Question Answering Competition (ALQAC) 2023, which focuses on enhancing legal
task performance by integrating classical statistical models and Pre-trained
Language Models (PLMs). For the document retrieval task, we implement a
pre-processing step to overcome input limitations and apply learning-to-rank
methods to consolidate features from various models. The question-answering
task is split into two sub-tasks: sentence classification and answer
extraction. We incorporate state-of-the-art models to develop distinct systems
for each sub-task, utilizing both classic statistical models and pre-trained
Language Models. Experimental results demonstrate the promising potential of
our proposed methodology in the competition.

该论文提出了 NOWJ1 团队在 2023 年自动法律问答竞赛中的方法，通过整合经典统计模型和预训练语言模型来提高法律任务性能。该方法使用了预处理步骤以克服输入的限制，并应用学习排序方法来整合来自不同模型的特征。问答任务被分为两个子任务：句子分类和答案抽取。我们将最先进的模型用于开发每个子任务的不同系统，并利用经典统计模型和预训练语言模型。实验结果表明该方法在竞赛中具有良好的潜力。

NOWJ1@ALQAC 2023：利用经典统计模型和预训练语言模型提升法律任务性能

NOWJ1@ALQAC 2023: Enhancing Legal Task Performance with Classic  Statistical Models and Pre-trained Language Models

We summarize the evaluation of the first Automated Legal Question Answering
Competition (ALQAC 2021). The competition this year contains three tasks, which
aims at processing the statute law document, which are Legal Text Information
Retrieval (Task 1), Legal Text Entailment Prediction (Task 2), and Legal Text
Question Answering (Task 3). The final goal of these tasks is to build a system
that can automatically determine whether a particular statement is lawful.
There is no limit to the approaches of the participating teams. This year,
there are 5 teams participating in Task 1, 6 teams participating in Task 2, and
5 teams participating in Task 3. There are in total 36 runs submitted to the
organizer. In this paper, we summarize each team's approaches, official
results, and some discussion about the competition. Only results of the teams
who successfully submit their approach description paper are reported in this
paper.

这篇论文总结了第一届自动法律问题回答竞赛 (ALQAC 2021) 的评估，该竞赛包含三个任务：法规文档处理、法律文本推理预测和法律问题回答，旨在建立一个能够自动确定某个陈述是否合法的系统。