This paper presents a new test collection for Legal IR, FALQU: Finding Answers to Legal Questions, where questions and answers were obtained from Law Stack Exchange (LawSE), a Q&A website for legal professionals, and others with experience in law. Much in line with Stack overflow, Law Stack Exchange has a variety of questions on different topics such as copyright, intellectual property, and criminal laws, making it an interesting source for dataset construction. Questions are also not limited to one country. Often, users of different nationalities may ask questions about laws in different countries and expertise. Therefore, questions in FALQU represent real-world users' information needs thus helping to avoid lab-generated questions. Answers on the other side are given by experts in the field. FALQU is the first test collection, to the best of our knowledge, to use LawSE, considering more diverse questions than the questions from the standard legal bar and judicial exams. It contains 9880 questions and 34,145 answers to legal questions. Alongside our new test collection, we provide different baseline systems that include traditional information retrieval models such as TF-IDF and BM25, and deep neural network search models. The results obtained from the BM25 model achieved the highest effectiveness.

翻译：本文介绍了用于法律信息检索的新测试集FALQU：寻找法律问题的答案，其中的问题和答案均来自Law Stack Exchange（LawSE）——一个面向法律专业人士及具有法律经验人士的问答网站。与Stack Overflow类似，Law Stack Exchange涵盖版权、知识产权和刑法等多种主题的问题，使其成为数据集构建的有趣来源。问题并不局限于单一国家，不同国籍的用户可能会询问关于不同国家法律及专业知识的问题。因此，FALQU中的问题代表了现实用户的信息需求，有助于避免实验室生成的问题。而答案则由该领域的专家提供。据我们所知，FALQU是首个使用LawSE的测试集，其问题比标准律师资格考试和司法考试的问题更加多样化。它包含9880个问题和34145个法律问题答案。除了这个新测试集，我们还提供了不同的基线系统，包括传统信息检索模型（如TF-IDF和BM25）以及深度神经网络搜索模型。BM25模型获得的结果达到了最高有效性。