以機器學習與規則方法辨識中文民事裁判書結構

Using Machine Learning and Pattern-Based Methods for Identifying Elements in Chinese Judgment Documents of Civil Cases

在建構法學資訊相關的分類模型或是推薦系統時，提供模型關於語料中與任務相關的輔助訊息有助於提升模型的效能及運算結果的可解釋性。在本研究中，我們選擇以人工智慧應用於法學資訊中較少見的民事訴訟案件作為研究對象。我們將「給付扶養費」相關的判決書依照其結構的功能性，找出聲請人所提出的主張、相對人所提出的答辯、法院對案件的見解及法院所引用的法條這四個部分，並從中抽取出該案件訴訟兩造的主要爭點。

Providing structural information about civil cases for judgement prediction systems or recommendation systems can enhance the efficiency of the inference procedures and the justifiability of produced results. In this research, we focus on the civil cases about alimony, which is a relatively uncommon choice in current applications of artificial intelligence in law. We attempt to identify the statements for four types of legal functions in judgement documents, i.e., the pleadings of the applicants, the responses of the opposite parties, the opinions of the courts, and uses of laws to reach the final decisions. In addition, we also try to identify the conflicting issues between the plaintiffs and the defendants in the judgement documents.