CAIL2019-SCM: A Dataset of Similar Case Matching in Legal Domain

Abstract

In this paper, we introduce CAIL2019-SCM, Chinese AI and Law 2019 Similar Case Matching dataset. CAIL2019-SCM contains 8,964 triplets of cases published by the Supreme People's Court of China. CAIL2019-SCM focuses on detecting similar cases, and the participants are required to check which two cases are more similar in the triplets. There are 711 teams who participated in this year's competition, and the best team has reached a score of 71.88. We have also implemented several baselines to help researchers better understand this task. The dataset and more details can be found from https://github.com/china-ai-law-challenge/CAIL2019/tree/master/scm.

arXiv comment5 pages

References in corpus (5)

• Enhanced LSTM for Natural Language Inference
• CAIL2018: A Large-Scale Legal Dataset for Judgment Prediction
• A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations
• Overview of CAIL2018: Legal Judgment Prediction Competition
• Event Identification as a Decision Process with Non-linear Representation of Text

Cited by in corpus (8)

• RoFormer: Enhanced Transformer with Rotary Position Embedding
• How Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence
• ERNIE-Doc: A Retrospective Long-Document Modeling Transformer
• Legal Element-oriented Modeling with Multi-view Contrastive Learning for Legal Case Retrieval
• MUSER: A Multi-View Similar Case Retrieval Dataset
• Domain-specific information retrieval
• VerbCL: A Dataset of Verbatim Quotes for Highlight Extraction in Case Law
• Indian Legal NLP Benchmarks : A Survey