RRepoGEO

REPOGEO REPORT · LITE

facebookresearch/BLINK

Default branch main · commit 5fe254dd · scanned 5/15/2026, 4:37:42 AM

GitHub: 1,208 stars · 234 forks

AI VISIBILITY SCORE
66 /100
Needs work
Category recall
1 / 2
Avg rank #2.0 when recommended
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface facebookresearch/BLINK, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • mediumreadme#1
    Strengthen the README's opening sentence to highlight deep learning and Wikipedia linking

    Why:

    CURRENT
    BLINK is an Entity Linking python library that uses Wikipedia as the target knowledge base.
    COPY-PASTE FIX
    BLINK is a state-of-the-art deep learning Python library for Entity Linking, specifically designed for Wikification (linking text mentions to Wikipedia entries) using advanced BERT-based architectures.
  • lowhomepage#2
    Add the primary research paper as the repository homepage

    Why:

    COPY-PASTE FIX
    https://arxiv.org/pdf/1911.03814.pdf

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
1 / 2
50% of queries surface facebookresearch/BLINK
Avg rank
#2.0
Lower is better. #1 = top recommendation.
Share of voice
6%
Of all named tools, what % are you?
Top rival
spaCy-entity-linker
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. spaCy-entity-linker · recommended 1×
  2. Wikipedia-API · recommended 1×
  3. WikiData-Toolkit · recommended 1×
  4. DBpedia Spotlight · recommended 1×
  5. NeuralCoref · recommended 1×
  • CATEGORY QUERY
    What Python libraries are available for linking text mentions to Wikipedia entries?
    you: not recommended
    AI recommended (in order):
    1. spaCy-entity-linker
    2. Wikipedia-API
    3. WikiData-Toolkit
    4. DBpedia Spotlight
    5. NeuralCoref

    AI recommended 5 alternatives but never named facebookresearch/BLINK. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a deep learning-based solution for end-to-end entity linking in text.
    you: #2
    AI recommended (in order):
    1. Hugging Face Transformers
    2. BLINK ← you
    3. mGEN
    4. OpenNRE
    5. spaCy
    6. spacy-transformers
    7. spacy-entity-linker
    8. DeepPavlov
    9. Flair
    10. PyTorch
    11. TensorFlow
    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of facebookresearch/BLINK?
    pass
    AI named facebookresearch/BLINK explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts facebookresearch/BLINK in production, what risks or prerequisites should they evaluate first?
    pass
    AI named facebookresearch/BLINK explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo facebookresearch/BLINK solve, and who is the primary audience?
    pass
    AI named facebookresearch/BLINK explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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MARKDOWN (README)
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HTML
<a href="https://repogeo.com/en/r/facebookresearch/BLINK"><img src="https://repogeo.com/badge/facebookresearch/BLINK.svg" alt="RepoGEO" /></a>
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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite