A law practitioner has to go through a lot of long legal case proceedings. To understand the motivation behind the actions of different parties/individuals in a legal case, it is essential that the parts of the document that express an intent corresponding to the case be clearly understood. In this paper, we introduce a dataset of 93 legal documents, belonging to the case categories of either Murder, Land Dispute, Robbery, or Corruption, where phrases expressing intent same as the category of the document are annotated. Also, we annotate fine-grained intents for each such phrase to enable a deeper understanding of the case for a reader. Finally, we analyze the performance of several transformer-based models in automating the process of extracting intent phrases (both at a coarse and a fine-grained level), and classifying a document into one of the possible 4 categories, and observe that, our dataset is challenging, especially in the case of fine-grained intent classification.

翻译：法律从业人员必须经历许多漫长的法律案件诉讼。为了理解不同当事人/个人在法律案件中的行为背后的动机,必须明确理解文件中表明与案件相应的意图的部分。在本文中,我们引入了93个法律文件的数据集,这些文件属于谋杀、土地纠纷、抢劫或腐败等案件类别,其中表达与文件类别相同的意图的短语附有附加说明。此外,我们注意到每个这类短语的细微区分意图,以便读者能够更深入地了解案件。最后,我们分析了几个基于变压器的模型在提取意图短语过程自动化(粗糙和细细细细的)以及将文件分类为可能的四个类别之一方面的性能,并指出,我们的数据集具有挑战性,特别是在精细的意向分类方面。