Rhetorical Role

Rhetorical role labeling (RRL) aims to automatically identify the semantic function of text segments within a document, such as arguments, facts, or rulings, particularly focusing on complex legal texts. Current research emphasizes improving RRL accuracy through techniques like hierarchical curriculum learning, leveraging analogous instances for knowledge transfer, and employing transformer-based models, often enhanced with graph neural networks or incorporating sentence position embeddings. This work is crucial for downstream tasks like legal document summarization, semantic search, and argument mining, ultimately improving efficiency and accessibility within the legal field and advancing natural language processing capabilities.