CLSep 15, 2025

PledgeTracker: A System for Monitoring the Fulfilment of Pledges

arXiv:2509.11804v11 citationsh-index: 2EMNLP
Originality Incremental advance
AI Analysis

This addresses the challenge for fact-checkers and political analysts in monitoring dynamic, multi-source pledge evidence, though it is incremental in improving existing methods.

The paper tackles the problem of tracking political pledge fulfilment by reformulating it as structured event timeline construction, and demonstrates that PledgeTracker effectively retrieves relevant evidence and reduces human verification effort in real-world workflows.

Political pledges reflect candidates' policy commitments, but tracking their fulfilment requires reasoning over incremental evidence distributed across multiple, dynamically updated sources. Existing methods simplify this task into a document classification task, overlooking its dynamic, temporal and multi-document nature. To address this issue, we introduce \textsc{PledgeTracker}, a system that reformulates pledge verification into structured event timeline construction. PledgeTracker consists of three core components: (1) a multi-step evidence retrieval module; (2) a timeline construction module and; (3) a fulfilment filtering module, allowing the capture of the evolving nature of pledge fulfilment and producing interpretable and structured timelines. We evaluate PledgeTracker in collaboration with professional fact-checkers in real-world workflows, demonstrating its effectiveness in retrieving relevant evidence and reducing human verification effort.

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