RRepoGEO

REPOGEO REPORT · LITE

atcbosselut/comet-commonsense

Default branch master · commit beb6b55c · scanned 6/6/2026, 11:58:01 AM

GitHub: 691 stars · 125 forks

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
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 atcbosselut/comet-commonsense, 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
    Start README with a clear project overview and value proposition

    Why:

    CURRENT
    To run a generation experiment (either conceptnet or atomic), follow these instructions:
    COPY-PASTE FIX
    This repository contains the official code for **COMET: Commonsense Transformers for Automatic Knowledge Graph Construction**, an ACL 2019 paper available at https://arxiv.org/abs/1906.05317. COMET introduces a generative model that leverages pre-trained language models to infer and produce new commonsense knowledge, expanding existing knowledge graphs like ATOMIC and ConceptNet.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    commonsense-reasoning, knowledge-graph, transformers, nlp, generative-ai, acl-2019, pytorch
  • mediumhomepage#3
    Add the paper URL as the repository homepage

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://arxiv.org/abs/1906.05317

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
0 / 2
0% of queries surface atcbosselut/comet-commonsense
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenIE
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenIE · recommended 1×
  2. IBM Watson Discovery · recommended 1×
  3. Google Cloud Knowledge Graph API · recommended 1×
  4. Amazon Comprehend · recommended 1×
  5. Ontotext-AD/graphdb-free · recommended 1×
  • CATEGORY QUERY
    How to automatically build a knowledge graph from unstructured text data?
    you: not recommended
    AI recommended (in order):
    1. OpenIE
    2. IBM Watson Discovery
    3. Google Cloud Knowledge Graph API
    4. Amazon Comprehend
    5. GraphDB (Ontotext-AD/graphdb-free)
    6. Protégé (protegeproject/protege)
    7. Haystack (deepset-ai/haystack)

    AI recommended 7 alternatives but never named atcbosselut/comet-commonsense. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help generate new commonsense knowledge using transformer models?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers Library
    2. PyTorch Lightning
    3. OpenAI API
    4. Google Cloud AI Platform / Vertex AI
    5. DeepSpeed
    6. Accelerate (Hugging Face)
    7. TensorFlow (with Keras)

    AI recommended 7 alternatives but never named atcbosselut/comet-commonsense. This is the gap to close.

    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 atcbosselut/comet-commonsense?
    pass
    AI named atcbosselut/comet-commonsense explicitly

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

  • If a team adopts atcbosselut/comet-commonsense in production, what risks or prerequisites should they evaluate first?
    pass
    AI named atcbosselut/comet-commonsense 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 atcbosselut/comet-commonsense solve, and who is the primary audience?
    pass
    AI did not name atcbosselut/comet-commonsense — 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

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atcbosselut/comet-commonsense — 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