RRepoGEO

REPOGEO REPORT · LITE

facebookresearch/BLINK

Default branch main · commit 5fe254dd · scanned 6/25/2026, 8:28:14 PM

GitHub: 1,211 stars · 233 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
62 /100
Needs work
Category recall
1 / 2
Avg rank #1.0 when recommended
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 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

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

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening sentence to highlight its Python library and SOTA capabilities

    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 Python library for Entity Linking, specifically designed to automatically map text mentions to Wikipedia entities (also known as Wikification) using advanced deep learning models.
  • hightopics#2
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    entity-linking, wikification, natural-language-processing, nlp, deep-learning, python, wikipedia, information-extraction, machine-learning, bert
  • mediumhomepage#3
    Add a homepage URL

    Why:

    COPY-PASTE FIX
    https://github.com/facebookresearch/BLINK#readme

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
#1.0
Lower is better. #1 = top recommendation.
Share of voice
6%
Of all named tools, what % are you?
Top rival
spaCy
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. spaCy · recommended 1×
  2. spacy-entity-linker · recommended 1×
  3. DBpedia Spotlight · recommended 1×
  4. pydbpedia-spotlight · recommended 1×
  5. Ambiverse NLU · recommended 1×
  • CATEGORY QUERY
    How can I automatically link text mentions to Wikipedia entities using a Python library?
    you: not recommended
    AI recommended (in order):
    1. spaCy
    2. spacy-entity-linker
    3. DBpedia Spotlight
    4. pydbpedia-spotlight
    5. Ambiverse NLU
    6. TagMe
    7. Hugging Face Transformers
    8. Wikipedia-API
    9. mwapi
    10. NLTK
    11. Stanza

    AI recommended 11 alternatives but never named facebookresearch/BLINK. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are state-of-the-art deep learning methods for end-to-end entity disambiguation in text?
    you: #1
    AI recommended (in order):
    1. BLINK ← you
    2. GENRE
    3. ELQ
    4. mGENRE
    5. LUKE
    6. REBEL
    7. Deep-ED
    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 did not name facebookresearch/BLINK — likely talking about a different project

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

Embed your GEO score

Drop this badge into the README of facebookresearch/BLINK. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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facebookresearch/BLINK — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite