Narrative Consolidation: Formulating a New Task for Unifying Multi-Perspective Accounts

TL;DR

This paper introduces Narrative Consolidation, a new NLP task focused on unifying overlapping narrative documents into a coherent, chronologically ordered account, emphasizing the importance of temporal structure for content fidelity.

Contribution

It formally defines Narrative Consolidation, proposes the Temporal Alignment Event Graph (TAEG) for modeling chronology, and demonstrates its effectiveness on biblical texts with perfect temporal ordering and significant content improvements.

Findings

Achieved perfect temporal ordering (Kendall's Tau of 1.000)

Significant improvement in ROUGE-L F1 (+357.2%)

Validated the importance of explicit temporal modeling

Abstract

Processing overlapping narrative documents, such as legal testimonies or historical accounts, often aims not for compression but for a unified, coherent, and chronologically sound text. Standard Multi-Document Summarization (MDS), with its focus on conciseness, fails to preserve narrative flow. This paper formally defines this challenge as a new NLP task: Narrative Consolidation, where the central objectives are chronological integrity, completeness, and the fusion of complementary details. To demonstrate the critical role of temporal structure in this task, we introduce Temporal Alignment Event Graph (TAEG), a graph structure that explicitly models chronology and event alignment. By applying a standard centrality algorithm to TAEG, our method functions as a version selection mechanism, choosing the most central representation of each event in its correct temporal position. In a study on the four Biblical Gospels, this structure-focused approach guarantees perfect temporal ordering (Kendall's Tau of 1.000) by design and dramatically improves content metrics (e.g., +357.2% in ROUGE-L F1). The success of this baseline method validates the formulation of Narrative Consolidation as a relevant task and establishes that an explicit temporal backbone is a fundamental component for its resolution.