RRepoGEO

REPOGEO REPORT · LITE

wainshine/Chinese-Names-Corpus

Default branch master · commit 47d4af8d · scanned 6/22/2026, 12:46:45 PM

GitHub: 4,304 stars · 1,008 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)

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

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 wainshine/Chinese-Names-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
    Explicitly state the license in the README

    Why:

    COPY-PASTE FIX
    本项目采用 Apache-2.0 许可证。详情请参阅仓库中的 LICENSE 文件。
  • highreadme#2
    Reposition the README's opening to clearly state the repo's primary purpose

    Why:

    CURRENT
    关于萌名（NameMoe）
萌名是一个基于大数据和自然语言处理技术的新取名产品。
通过分词工具对海量文本进行分词和词频统计。数据清洗后，得到千万级的人名词典。再对其进行性别、年龄、拼音、情感、人名指数等标记，最终形成5600万+的中文人名图谱。
本子项目可用于中文分词、人名识别等场景。
    COPY-PASTE FIX
    本项目是一个综合性的中文人名语料库（Chinese-Names-Corpus），包含中文、英文、日文人名数据，以及姓氏、称呼和成语词典。它可用于中文分词、人名实体识别、人名生成等NLP和机器学习任务。本语料库是萌名（NameMoe）产品的基础数据之一。
  • mediumtopics#3
    Add topics related to name generation and NLP/ML

    Why:

    CURRENT
    corpus, dataset, dict, names, ner
    COPY-PASTE FIX
    corpus, dataset, dict, names, ner, name-generator, nlp, machine-learning, data-science, generation

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 wainshine/Chinese-Names-Corpus
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Baidu Baike
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Baidu Baike · recommended 1×
  2. Wikipedia Dumps · recommended 1×
  3. LDC (Linguistic Data Consortium) · recommended 1×
  4. Hugging Face Datasets · recommended 1×
  5. Faker · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive dataset of Chinese names for NLP tasks?
    you: not recommended
    AI recommended (in order):
    1. Baidu Baike
    2. Wikipedia Dumps
    3. LDC (Linguistic Data Consortium)
    4. Hugging Face Datasets

    AI recommended 4 alternatives but never named wainshine/Chinese-Names-Corpus. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools can generate realistic names across multiple languages for testing purposes?
    you: not recommended
    AI recommended (in order):
    1. Faker
    2. Chance.js (chancejs/chancejs)
    3. Bogus (bchavez/Bogus)
    4. mimesis (mimesis-project/mimesis)
    5. Mockaroo
    6. Random User Generator
    7. Data Faker (datafaker-net/datafaker)

    AI recommended 7 alternatives but never named wainshine/Chinese-Names-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 wainshine/Chinese-Names-Corpus?
    pass
    AI did not name wainshine/Chinese-Names-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?

  • If a team adopts wainshine/Chinese-Names-Corpus in production, what risks or prerequisites should they evaluate first?
    pass
    AI named wainshine/Chinese-Names-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 wainshine/Chinese-Names-Corpus solve, and who is the primary audience?
    pass
    AI named wainshine/Chinese-Names-Corpus 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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wainshine/Chinese-Names-Corpus — 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