用时间线比对法精准验证含复杂时间关系的虚假信息
ChronoFact: Timeline-based Temporal Fact Verification
- 将事实和证据事件按时间轴排列，系统比对时序关系
- 在新构建的数据集上准确率显著优于现有方法
- 适合需要分析多事件时间逻辑的新闻审核场景
时间性陈述常包含错误信息，是数字时代虚假信息传播的主要挑战。现有的事实核查系统难以应对包含多个重叠或重复事件的时间性陈述。本文提出一种基于时间线的事实验证框架，从陈述和证据中识别事件，并分别组织成时间序列。该框架系统分析陈述与证据中事件之间的时序关系，判断每个事件的真实性及其时间准确性，从而确定整个陈述的真伪。同时，我们构建了一个新的复杂时间性陈述数据集，用于训练和评估该框架。实验结果表明，该方法能有效处理时间性陈述验证中的复杂问题。
原文摘要 · Abstract (English)
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 timeline-based reasoning for the training and evaluation of our proposed framework. Experimental results demonstrate the effectiveness of our approach in handling the intricacies of temporal claim verification.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。