# Factual Inconsistencies in Multilingual Wikipedia Tables

arXiv: https://arxiv.org/abs/2507.18406 · HTML: https://mlsanity.com/paper/2507.18406/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 17 references that are in the map.
- First posted on arXiv 24 Jul 2025.

## Builds on (most cited first, 9 of 9)

- [Language (Technology) is Power: A Critical Survey of "Bias" in NLP](https://mlsanity.com/paper/2005.14050/) (2020)
- [A Survey on Data Selection for Language Models](https://mlsanity.com/paper/2402.16827/) (2024)
- [DLAMA: A Framework for Curating Culturally Diverse Facts for Probing the Knowledge of Pretrained Language Models](https://mlsanity.com/paper/2306.05076/) (2023)
- [Extracting Novel Facts from Tables for Knowledge Graph Completion (Extended version)](https://mlsanity.com/paper/1907.00083/) (2019)
- [Analyzing Race and Country of Citizenship Bias in Wikidata](https://mlsanity.com/paper/2108.05412/) (2021)
- [Tab2Know: Building a Knowledge Base from Tables in Scientific Papers](https://mlsanity.com/paper/2107.13306/) (2021)
- [Uncertainty Management in the Construction of Knowledge Graphs: a Survey](https://mlsanity.com/paper/2405.16929/) (2024)
- [Architecture for a multilingual Wikipedia](https://mlsanity.com/paper/2004.04733/) (2020)
- [Leveraging LLM For Synchronizing Information Across Multilingual Tables](https://mlsanity.com/paper/2504.02559/) (2025)

## Built on by (most cited first, 1 of 1)

- [Convergence in Science, Divergence in Religion: Calibrated Framing Differences Across Wikipedia's Language Editions](https://mlsanity.com/paper/2608.21821/) (2026)

## Abstract (arXiv)

Wikipedia serves as a globally accessible knowledge source with content in over 300 languages. Despite covering the same topics, the different versions of Wikipedia are written and updated independently. This leads to factual inconsistencies that can impact the neutrality and reliability of the encyclopedia and AI systems, which often rely on Wikipedia as a main training source. This study investigates cross-lingual inconsistencies in Wikipedia's structured content, with a focus on tabular data. We developed a methodology to collect, align, and analyze tables from Wikipedia multilingual articles, defining categories of inconsistency. We apply various quantitative and qualitative metrics to assess multilingual alignment using a sample dataset. These insights have implications for factual verification, multilingual knowledge interaction, and design for reliable AI systems leveraging Wikipedia content.