# An Explainable Coherence Score for Detecting Temporal Inconsistencies in Political News

arXiv: https://arxiv.org/abs/2608.29175 · HTML: https://mlsanity.com/paper/2608.29175/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 24 references that are in the map.
- First posted on arXiv 29 Aug 2026.

## Builds on (most cited first, 10 of 10)

- [FEVER: a large-scale dataset for Fact Extraction and VERification](https://mlsanity.com/paper/1803.05355/) (2018)
- ["Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection](https://mlsanity.com/paper/1705.00648/) (2017)
- [FakeNewsNet: A Data Repository with News Content, Social Context and Spatialtemporal Information for Studying Fake News on Social Media](https://mlsanity.com/paper/1809.01286/) (2018)
- [A Survey on Temporal Knowledge Graph: Representation Learning and Applications](https://mlsanity.com/paper/2403.04782/) (2024)
- [Worse than Zero-shot? A Fact-Checking Dataset for Evaluating the Robustness of RAG Against Misleading Retrievals](https://mlsanity.com/paper/2502.16101/) (2025)
- [Time-Aware Evidence Ranking for Fact-Checking](https://mlsanity.com/paper/2009.06402/) (2020)
- [Implicit Temporal Reasoning for Evidence-Based Fact-Checking](https://mlsanity.com/paper/2302.12569/) (2023)
- [ChronoFact: Timeline-based Temporal Fact Verification](https://mlsanity.com/paper/2410.14964/) (2024)
- [MCP-Orchestrated Multi-Agent System for Automated Disinformation Detection](https://mlsanity.com/paper/2508.10143/) (2025)
- [TSVer: A Benchmark for Fact Verification Against Time-Series Evidence](https://mlsanity.com/paper/2511.01101/) (2025)

## Abstract (arXiv)

Temporal inconsistencies, such as mandates attributed outside their real interval, events presented as past before they occurred, or inverted causal sequences, are a form of political disinformation that evades style-based fake news detectors: a well-written article with a single wrong date carries no lexical signal of falsehood. This paper introduces the Temporal Coherence Score (TCS), a continuous, intrinsically interpretable metric that quantifies the temporal coherence of a news article, computed by a four-stage pipeline: extraction of temporal facts, construction of a temporal knowledge graph, hierarchical verification against internal consistency rules and external reference sources, and score aggregation with automatically generated explanations. Verification combines eight internal checkers derived from Allen's interval algebra with a five-level external hierarchy ranging from a locally stored reference knowledge base of 1{,}256 curated political facts to live Wikidata SPARQL queries. On a benchmark of 100 political news articles with injected temporal errors, the system reaches a precision of 0.909 at the selected operating threshold, with a single residual false positive, a profile deliberately tuned for human-in-the-loop fact-checking assistance, where false alarms are costlier than missed detections. Unlike lexical baselines that output only a binary label, every flagged article is accompanied by the inconsistency type, the entities involved, and the reference source that contradicts the claim.