wikipedia2vec
A tool for learning vector representations of words and entities from Wikipedia
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
37views this month
Decision brief
A Python-based tool for generating embeddings derived from Wikipedia content.
Good fit when
- You need to generate word and entity embeddings based on extensive Wikipedia data
- Your project focuses specifically on leveraging Wikipedia's breadth of knowledge in NLP tasks
Avoid when
- Your dataset doesn't intersect with or benefit from Wikipedia content
- You require real-time updating capabilities that exceed static Wikipedia dumps
Observed Jul 12, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Dormant (869d since push)
- As of Sep 20, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 20, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install wikipedia2vecSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
wikipedia2vec is a Python-based tool designed to generate embeddings for words and entities derived from Wikipedia content, aiding in natural language processing tasks like text classification.
Capability facts
- Languages
- python
Source: github.language+pyproject.toml · Sep 20, 2026
Categories
Tags
README
License Apache License 2.0
For agents
This page has a .md twin and JSON over the API.