CoPERLex: Content Planning with Event-based Representations for Legal Case Summarization
This addresses the challenge for legal professionals in efficiently summarizing lengthy judgments, though it appears incremental by building on existing summarization methods with event-centric representations.
The paper tackled the problem of legal case summarization by proposing CoPERLex, a framework that integrates content selection and event-based planning, and demonstrated its effectiveness on four datasets with advantages over entity-centric approaches.
Legal professionals often struggle with lengthy judgments and require efficient summarization for quick comprehension. To address this challenge, we investigate the need for structured planning in legal case summarization, particularly through event-centric representations that reflect the narrative nature of legal case documents. We propose our framework, CoPERLex, which operates in three stages: first, it performs content selection to identify crucial information from the judgment; second, the selected content is utilized to generate intermediate plans through event-centric representations modeled as Subject-Verb-Object tuples; and finally, it generates coherent summaries based on both the content and the structured plan. Our experiments on four legal summarization datasets demonstrate the effectiveness of integrating content selection and planning components, highlighting the advantages of event-centric plans over traditional entity-centric approaches in the context of legal judgements.