Wembedder: Wikidata entity embedding web service
Finn {\AA}rup Nielsen

TL;DR
Wembedder is a web service providing multilingual embeddings for over 600,000 Wikidata entities, trained using graph walks and accessible via a REST API, facilitating easier access to structured knowledge representations.
Contribution
It introduces a publicly accessible web service for Wikidata entity embeddings, integrating graph-based training with multilingual support and API access.
Findings
Supports over 600,000 Wikidata items and properties
Uses Gensim Word2Vec with graph walks for embedding training
Provides a REST API for easy access
Abstract
I present a web service for querying an embedding of entities in the Wikidata knowledge graph. The embedding is trained on the Wikidata dump using Gensim's Word2Vec implementation and a simple graph walk. A REST API is implemented. Together with the Wikidata API the web service exposes a multilingual resource for over 600'000 Wikidata items and properties.
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Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Semantic Web and Ontologies
