RRepoGEO

REPOGEO REPORT · LITE

PlexPt/chatgpt-corpus

Default branch main · commit fd6606c4 · scanned 6/4/2026, 8:06:59 AM

GitHub: 962 stars · 145 forks

AI VISIBILITY SCORE
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 PlexPt/chatgpt-corpus, 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 README's H1 to specify LLM fine-tuning purpose

    Why:

    CURRENT
    # chatgpt-corpus
chatgpt 中文语料库
    COPY-PASTE FIX
    # chatgpt-corpus

一个大型的、由ChatGPT生成的中文语料库，专为训练和微调大型语言模型（LLMs）设计，包含对话、小说和客服问答数据。
  • mediumtopics#2
    Add more specific topics for LLM training and data types

    Why:

    CURRENT
    awesome, corpus, corpus-data, question-answering
    COPY-PASTE FIX
    corpus, corpus-data, chinese-nlp, llm-training, fine-tuning, conversational-ai, customer-service-data, novel-generation, chatgpt-data
  • lowreadme#3
    Add a brief section differentiating the corpus from general datasets

    Why:

    COPY-PASTE FIX
    ## 为什么选择本语料库？

本语料库专注于提供由ChatGPT生成的大规模中文对话、小说和客服问答数据，特别适合需要特定风格或领域数据进行模型微调的研究者和开发者。与通用大型语料库相比，我们提供的是经过筛选和结构化的、直接可用于生成式AI训练的特定类型数据。

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 PlexPt/chatgpt-corpus
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
huggingface/datasets
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/datasets · recommended 1×
  2. Tencent AI Lab · recommended 1×
  3. Baidu NLP · recommended 1×
  4. LDC (Linguistic Data Consortium) · recommended 1×
  5. Common Crawl · recommended 1×
  • CATEGORY QUERY
    Where can I find large Chinese text datasets for training AI language models?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Datasets (huggingface/datasets)
    2. Tencent AI Lab
    3. Baidu NLP
    4. LDC (Linguistic Data Consortium)
    5. Common Crawl
    6. cc_net (facebookresearch/cc_net)
    7. Wikipedia Dumps
    8. OpenSubtitles

    AI recommended 8 alternatives but never named PlexPt/chatgpt-corpus. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need conversational and customer service Chinese data to fine-tune generative AI models.
    you: not recommended
    AI recommended (in order):
    1. TencentPretrain
    2. CLUECorpus
    3. Baidu Wenxin ERNIE Datasets
    4. Alibaba Conversational AI Datasets
    5. Zhihu
    6. Weibo
    7. Taobao
    8. JD.com

    AI recommended 8 alternatives but never named PlexPt/chatgpt-corpus. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 PlexPt/chatgpt-corpus?
    pass
    AI named PlexPt/chatgpt-corpus explicitly

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

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

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