RRepoGEO

REPOGEO REPORT · LITE

taishan1994/awesome-chinese-ner

Default branch main · commit ae6638b2 · scanned 6/10/2026, 10:22:43 AM

GitHub: 773 stars · 59 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
22 /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
1 / 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 taishan1994/awesome-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 README's opening sentence to state it's an 'awesome list'

    Why:

    CURRENT
    # awesome-chinese-ner
中文命名实体识别
    COPY-PASTE FIX
    # awesome-chinese-ner
一个精选的中文命名实体识别（NER）资源列表，包含最新论文、工具、数据集和预训练模型等。
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT or Apache-2.0) in the repository root to clarify usage rights.
  • mediumtopics#3
    Add 'awesome-list' and 'chinese-nlp-resources' to topics

    Why:

    CURRENT
    named-entity-recognition, ner
    COPY-PASTE FIX
    named-entity-recognition, ner, awesome-list, chinese-nlp-resources

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 taishan1994/awesome-chinese-ner
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers Library
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers Library · recommended 2×
  2. Stanford CoreNLP · recommended 2×
  3. spaCy · recommended 1×
  4. Jieba · recommended 1×
  5. FudanNLP · recommended 1×
  • CATEGORY QUERY
    What are the best resources for performing named entity recognition on Chinese text?
    you: not recommended
    AI recommended (in order):
    1. spaCy
    2. Hugging Face Transformers Library
    3. Stanford CoreNLP
    4. Jieba
    5. FudanNLP
    6. HanLP

    AI recommended 6 alternatives but never named taishan1994/awesome-chinese-ner. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I implement named entity recognition for Chinese using large language models?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers Library
    2. bert-base-chinese
    3. hfl/chinese-bert-wwm-ext
    4. uer/t5-v1_1-chinese-base
    5. THUDM/chatglm2-6b
    6. THUDM/chatglm3-6b
    7. PaddleNLP
    8. ernie-3.0-base-zh
    9. ernie-gram-zh
    10. ernie-m-base
    11. OpenNMT-py
    12. Stanford CoreNLP
    13. Spacy
    14. zh_core_web_trf

    AI recommended 14 alternatives but never named taishan1994/awesome-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 taishan1994/awesome-chinese-ner?
    pass
    AI did not name taishan1994/awesome-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 taishan1994/awesome-chinese-ner in production, what risks or prerequisites should they evaluate first?
    pass
    AI named taishan1994/awesome-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 taishan1994/awesome-chinese-ner solve, and who is the primary audience?
    pass
    AI did not name taishan1994/awesome-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?

Embed your GEO score

Drop this badge into the README of taishan1994/awesome-chinese-ner. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/taishan1994/awesome-chinese-ner.svg)](https://repogeo.com/en/r/taishan1994/awesome-chinese-ner)
HTML
<a href="https://repogeo.com/en/r/taishan1994/awesome-chinese-ner"><img src="https://repogeo.com/badge/taishan1994/awesome-chinese-ner.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

taishan1994/awesome-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