ChronoFact: Timeline-based Temporal Fact Verification
Anab Maulana Barik, Wynne Hsu, Mong Li Lee

TL;DR
ChronoFact is a novel timeline-based framework for verifying complex temporal claims by organizing events into chronological timelines and assessing their relationships, significantly improving accuracy in misinformation detection.
Contribution
Introduces a new timeline-based verification framework and dataset for complex temporal claims, enhancing the evaluation of temporal fact accuracy.
Findings
Effective in handling overlapping and recurring events
Outperforms existing methods in temporal claim verification
Provides a new dataset for training and evaluation
Abstract
Temporal claims, often riddled with inaccuracies, are a significant challenge in the digital misinformation landscape. Fact-checking systems that can accurately verify such claims are crucial for combating misinformation. Current systems struggle with the complexities of evaluating the accuracy of these claims, especially when they include multiple, overlapping, or recurring events. We introduce a novel timeline-based fact verification framework that identify events from both claim and evidence and organize them into their respective chronological timelines. The framework systematically examines the relationships between the events in both claim and evidence to predict the veracity of each claim event and their chronological accuracy. This allows us to accurately determine the overall veracity of the claim. We also introduce a new dataset of complex temporal claims involving…
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Taxonomy
TopicsNatural Language Processing Techniques · Advanced Text Analysis Techniques · Web Data Mining and Analysis
