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GSAT-7000-Anki

Let's generate some GSAT English Anki decks with the help of AI! (WIP) （學測英文 7000 單字）
Open repo on GitHubgithub.com/Clydinite/GSAT-7000-Anki
Python · ★ 1 · 0 forks · MIT · paperwork by the Cap'mmostly ai (inferred)light human (inferred)works-on-my-machine (inferred)other
listed 1 hour ago by Clydinite · last checked 9 minutes ago
The owner didn't write this. This repo never submitted itself. The Cap'm found it on a truffle trawl and wrote its paperwork from what GitHub already shows. Picked by hand by the Cap'm on 2026-09-26: Let's generate some GSAT English Anki decks with the help of AI! (WIP) （學測英文 7000 單字）; its own README says "Data Source The vocabulary data is taken from CEEC ( Acknowledgements The deck is entirely AI-generated and provided as-is". 1 stars; MIT license. The owner did not submit this. Votes count; awards don't until the owner claims it.

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GitHub says
Let's generate some GSAT English Anki decks with the help of AI! (WIP) （學測英文 7000 單字）
created
2026-01-21 · pushed 2 months ago · 205 commits · 1 contributor
languages
Python 86%CSS 11%HTML 3%
paperwork
licensereadme 42% health
dependencies
no dependency graph (no manifest, or disabled) · OSV.dev, checked 1 hour ago

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The Cap'm wrote this paperwork, not the owner. This repo never submitted itself to SlopScore. The Cap'm picked it by hand: Let's generate some GSAT English Anki decks with the help of AI! (WIP) （學測英文 7000 單字）; its own README says "Data Source The vocabulary data is taken from CEEC ( Acknowledgements The deck is entirely AI-generated and provided as-is". It carries the MIT license. The disclosures above are his best guess from what GitHub shows.

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README — the repo's own words, folded up so the grading fits on one screen

GSAT English Vocabulary

This repository contains a collection of vocabulary for GSAT listed in data/ directory, along with generated TSV for Anki. Templates and stylings are also provided.

The project uses a sense-based approach to ensure all common meanings of a word are covered, with a strong focus on collocations to help students learn how words are actually used in context.

The cards are currently under development. I would appreciate support on additional card generations or corrections.

Card Content

Front Side

  • Headword

Back Side

  • Headword
  • Meta-section: (Reveal)
    • General explanation
    • Conjugations & Morphology
    • Related words
  • Senses:
    • Sense pattern and translation (Always visible)
    • A "Reveal" button that shows:
      • Collocation patterns and their translations
      • Usage explanations
      • Example sentences with translations
      • Synonyms and Antonyms

Card Backside Sense Reveal Meta Section

Card Status

Currently I have completed the following cards (on this branch):

  • Level 1 - 0/1013
  • Level 2 - 0/1003
  • Level 3 - 1002/1002
  • Level 4 - 1002/1002
  • Level 5 - 200/1002
  • Level 6 - 0/1008

The remaining levels are yet to be generated. You can help by generating cards for any level (probably level 5 would be the best). Simply use the --level X flag on python process.py (e.g. python process.py --level 5). However, a Gemini API key is required (change the .env.example to .env and fill in the API key), which can be obtained for free on Google AI Studio.

All sentences are marked with <pattern> ... </pattern> and <target> ... </target> tags. The target words are marked with <target> ... </target> tags, while the collocation words are marked with <pattern> ... </pattern> tags.

There's currently a high amount of cards with errors in <pattern> ... </pattern> markings. I'm working on cleaning them up.

Project Structure

  • data/vocabulary/: Source word lists for each level.
  • data/raw/: Raw Gemini API responses in TSV format (level-specific), it includes <pattern> and <target> markers.
  • data/Anki/: Formatted TSV files ready for Anki import. (generated via to_anki.py)
  • templates/: HTML and CSS for the cards.

How to Contribute

The remaining levels are yet to be generated. You can help by generating cards for any unfinished level:

  1. Setup: Clone the repo and install dependencies.
  2. API Key: Change .env.example to .env and fill in your Gemini API key from Google AI Studio.
  3. Generate: Run python process.py --level X to generate the raw data.
  4. Verify & Fix: Run python verify.py --level X to find errors and python edit.py --level X to fix them (this is powered by AI also).
  5. Export: Run python to_anki.py --level X to generate the Anki import file in data/Anki/.
  6. Preview: Run python preview.py to verify card styling and reveal functionality locally before import.
  7. Submit: Create a Pull Request on GitHub with the new files in data/raw/ and data/Anki/.

Data Source

The vocabulary data is taken from CEEC.

Acknowledgements

The deck is entirely AI-generated and provided as-is. Please be mindful of potential AI hallucinations or errors. Use this resource to supplement your studies, but verify critical information with a primary source.

Read the rest on GitHub

Scan report · 2026-09-26
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