We propose a simple approach for the abstractive summarization of long legal opinions that considers the argument structure of the document. Legal opinions often contain complex and nuanced argumentation, making it challenging to generate a concise summary that accurately captures the main points of the legal opinion. Our approach involves using argument role information to generate multiple candidate summaries, then reranking these candidates based on alignment with the document's argument structure. We demonstrate the effectiveness of our approach on a dataset of long legal opinions and show that it outperforms several strong baselines.

翻译：我们提出了一种针对长法律意见书的简洁抽象摘要方法，该方法考虑了文档的论点结构。法律意见书通常包含复杂且微妙的论证过程，这使得生成能够准确捕捉法律意见核心要点的简洁摘要颇具挑战。我们的方法利用论点角色信息生成多个候选摘要，随后根据这些候选摘要与文档论点结构的对齐程度对其进行重排序。我们在一个长法律意见书数据集上展示了该方法的有效性，并证明其优于多个强基线模型。