Papers
arxiv:2609.08508

WiDiff: Extracting Changes from Wikidata's Edit History

Published on Sep 8
Authors:
,
,
,

Abstract

WiDiff enables large-scale analytical queries over Wikidata's complete edit history by extracting and unifying its change data.

Knowledge graphs have become a key resource for integrating heterogeneous data and powering downstream tasks such as question answering, entity linking, and semantic search. They are built and maintained incrementally, either (i) fully automated, e.g., YAGO, (ii) semiautomatically with community oversight, e.g., DBpedia, or (iii) manually through collaborative editing, e.g., Wikidata. Understanding the evolution of knowledge graphs is essential as changes may reflect real-world updates, error corrections, or noise introduced by vandalism, all of which affect the reliability of downstream applications. Among openly available knowledge graphs, Wikidata is the most challenging case to study evolution, with over 120 million entities edited by humans and bots and an edit history spanning more than a decade. Although Wikidata exposes change data in various formats (e.g., periodic dumps and real-time event streams), none support analytical queries over the complete edit history. Therefore, we present WiDiff, a tool that extracts changes from Wikidata's complete edit history and provides a unified interface for large-scale analytical queries over it.

Community

Sign up or log in to comment

Get this paper in your agent:

hf papers read 2609.08508
Don't have the latest CLI?
curl -LsSf https://hf.co/cli/install.sh | bash

Models citing this paper 0

No model linking this paper

Cite arxiv.org/abs/2609.08508 in a model README.md to link it from this page.

Datasets citing this paper 1

Spaces citing this paper 0

No Space linking this paper

Cite arxiv.org/abs/2609.08508 in a Space README.md to link it from this page.

Collections including this paper 0

No Collection including this paper

Add this paper to a collection to link it from this page.