RRepoGEO

REPOGEO REPORT · LITE

ProHiryu/bert-chinese-ner

Default branch master · commit 96efd234 · scanned 5/31/2026, 11:48:14 PM

GitHub: 976 stars · 276 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 ProHiryu/bert-chinese-ner, 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
    Clarify the README's opening statement and remove confusing 'PS' note

    Why:

    CURRENT
    ## 前言

使用预训练语言模型BERT做中文NER尝试，fine - tune BERT模型

PS: 移步最新**albert fine-tune ner**模型
    COPY-PASTE FIX
    ## 前言

本项目提供了一个使用预训练语言模型BERT进行中文命名实体识别 (NER) 的完整实现，并演示了如何对BERT模型进行微调。
  • hightopics#2
    Expand repository topics for better categorization

    Why:

    CURRENT
    bert, chinese, fine-tune, ner, tensorflow
    COPY-PASTE FIX
    bert, chinese-ner, named-entity-recognition, fine-tuning, tensorflow, deep-learning, nlp, chinese-nlp, bert-finetuning, tensorflow-implementation
  • mediumhomepage#3
    Add a homepage URL to the About section

    Why:

    COPY-PASTE FIX
    https://github.com/ProHiryu/bert-chinese-ner

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 ProHiryu/bert-chinese-ner
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ERNIE
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ERNIE · recommended 2×
  2. Hugging Face Transformers · recommended 1×
  3. BERT · recommended 1×
  4. RoBERTa · recommended 1×
  5. ELECTRA · recommended 1×
  • CATEGORY QUERY
    How to perform named entity recognition on Chinese text using deep learning models?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. BERT
    3. RoBERTa
    4. ELECTRA
    5. XLM-RoBERTa
    6. PaddleNLP
    7. PaddlePaddle
    8. ERNIE
    9. spaCy
    10. Keras
    11. TensorFlow
    12. PyTorch
    13. Flair
    14. Word2Vec
    15. GloVe
    16. FastText
    17. ELMo

    AI recommended 17 alternatives but never named ProHiryu/bert-chinese-ner. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good approaches for fine-tuning BERT models for Chinese NLP tasks?
    you: not recommended
    AI recommended (in order):
    1. BERT-base-Chinese
    2. MacBERT
    3. RoBERTa-wwm-ext-large-Chinese
    4. ERNIE
    5. ELECTRA-Chinese
    6. Chinese-BERT-WWM

    AI recommended 6 alternatives but never named ProHiryu/bert-chinese-ner. 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 ProHiryu/bert-chinese-ner?
    pass
    AI did not name ProHiryu/bert-chinese-ner — 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 ProHiryu/bert-chinese-ner in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ProHiryu/bert-chinese-ner 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 ProHiryu/bert-chinese-ner solve, and who is the primary audience?
    pass
    AI named ProHiryu/bert-chinese-ner explicitly

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

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ProHiryu/bert-chinese-ner — 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