# Wikidata-lite for Knowledge Extraction and Exploration

arXiv: https://arxiv.org/abs/2211.05416 · HTML: https://mlsanity.com/paper/2211.05416/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Nov 2022.

## Built on by (most cited first, 4 of 4)

- [Multimodal Cultural Heritage Knowledge Graph Extension with Language and Vision Models](https://mlsanity.com/paper/2605.17669/) (2026)
- [A Practical Entity Linking System for Tables in Scientific Literature](https://mlsanity.com/paper/2306.10044/) (2023)
- [OntoKG: Ontology-Oriented Knowledge Graph Construction with Intrinsic-Relational Routing](https://mlsanity.com/paper/2604.02618/) (2026)
- [Categorizing Mathematical Concepts with LLM Voting Ensembles in Mathswitch](https://mlsanity.com/paper/2606.28815/) (2026)

## Abstract (arXiv)

Wikidata is the largest collaborative general knowledge graph supported by a worldwide community. It includes many helpful topics for knowledge exploration and data science applications. However, due to the enormous size of Wikidata, it is challenging to retrieve a large amount of data with millions of results, make complex queries requiring large aggregation operations, or access too many statement references. This paper introduces our preliminary works on Wikidata-lite, a toolkit to build a database offline for knowledge extraction and exploration, e.g., retrieving item information, statements, provenances, or searching entities by their keywords and attributes. Wikidata-lite has high performance and memory efficiency, much faster than the official Wikidata SPARQL endpoint for big queries. The Wikidata-lite repository is available at https://github.com/phucty/wikidb.