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.
Wikidata-lite for Knowledge Extraction and Exploration
Wikidata-lite is an offline toolkit for efficient knowledge extraction and exploration from Wikidata, offering high performance and memory efficiency for large queries.
- Year
- 2022
- Venue
- arXiv 2022
- Authors
- 2
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- Abstract onlyARXIV-DEFAULT
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- Abstract & full text
- arxiv.org/abs/2211.05416ARXIV-DEFAULT
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