Overview

What is Quinglish, Anyway? Quinglish is a fast-track way to learn English by collecting the “best hacks” from real learners—phrases, shortcuts, and workarounds that actually get you talking. It’s less about grammar drills and more about conversation, fun, and sharing tricks that work in the real world.

Want to Help Shape Quinglish?

Quinglish is still cooking. I’m looking for curious people to:
• Try it early as a beta tester
• Share input on lesson design / pedagogy or coding/development.
• Or just ask questions and stay in the loop

If that sounds like you, drop your info below — I’ll reach out when the time’s right.

Get Involved
Core Concepts
  • Modern Phrase Theory: modular phrase tokens; buddy‑clauses; telegraphic ↔ ornate.
  • Moonwalk Method: rhythmic back‑chaining drills; layered repetition.
  • NPC Scenarios: Airport Bardo; restaurant; rentals; small talk.
  • Ciatric: semantic event bus (#SEB), tagging, embeddings, RAG.
  • Ciatric Search: advanced search capabilities using semantic understanding is basically a collection of AI models that will aggressively capture your data and use it to fine-tune a private language model. Champion your own data while keeping it locked down-no cloud services. But that will come when the ESL Project is finished. message me if you cant wait.
Modern Phrase Theory

What is a Buddy Clause?

A buddy clause is a short, modular, self-contained phrase that can be used independently or “snapped” onto another clause to build more complex sentences. Think of them as Lego blocks for spoken English: each block makes sense on its own and can easily combine with others to expand meaning, add detail, or clarify context.

Example:

“As a young man living in the United States, Mark used to dream of walking the streets of Paris.”
  • Buddy clause: “As a young man living in the United States”
  • Main clause: “Mark used to dream of walking the streets of Paris.”

Purpose of the Buddy Clause

  1. Gives you a starting point:
    Buddy clauses give learners something—anything—to say. They’re a way to break the ice, set a rhythm, and give your speech forward motion (think jazz: even if you don’t know the whole song, you’ve got the groove). A good start builds confidence and helps to focus the mind of the speaker and the attention of the listener.
  2. Aids comprehension:
    Buddy clauses usually come first and establish a timeframe, location, or point of view—like “Once upon a time, in Hollywood…” or “As a young man living in the United States…” This sets up whatever action, feeling, or story comes next. In a sense, the buddy clause acts as the antecedent, making what follows feel anchored and meaningful.
  3. Encourages flexible, modular thinking:
    Like building with Lego blocks, learners can “plug and play” buddy clauses, swap parts in and out, and remix them to fit the moment. This mirrors how native speakers naturally elaborate, clarify, or riff in conversation.
  4. Bridges telegraphic and natural English:
    Buddy clauses help learners go from “barebones” or “telegraphic” English (e.g., “When young man he dream about Paris”) to more natural, native-like phrasing—without feeling overwhelmed. They’re the missing link between “simple words” and “real talk.”
  5. Mirrors spoken conversation:
    In speech, people often layer “buddy” clauses for nuance:
    “Well, as I said yesterday, if it rains, I’ll just stay home.”
    • “as I said yesterday” = buddy clause
    • “if it rains” = conditional/subordinate clause
    • “I’ll just stay home” = main clause

#Quinglish #BuddyClause #ModularEnglish #Chunking #ESL #PhraseBlocks

Let me know if you want more technical examples or want to see how to teach these with NPCs in a role-play!

Quinglish (Phrase‑Based English)

Quinglish is a phrase-based approach to English that focuses on chunks of language—ready-to-use phrases, sentence stems, and conversational building blocks—rather than individual vocabulary words or abstract grammar rules. Learners treat these as modular “tokens” they can snap together, remix, and adapt in real time.

Goals of Quinglish

  • Get talking faster: Build fluency by practicing conversational units you can actually use, not memorizing irregular verb charts.
  • Share the hacks: Every learner contributes tricks, phrases, and insights that worked for them; Quinglish grows as a living, crowd-sourced toolkit.
  • Make it fun: Prioritize dialogue, humor, and play over rote drills so the language- people learn languages better this way.

Tokenizer & Tokens

Example Tokenization

# Example JSON tokenization (edit with real examples)
{
  "id": "ex-001",
  "input": "I go store yesterday. Buy apples. No good.",
  "tokens": [
    {"t": "actor", "v": "I"},
    {"t": "action", "v": "go", "tense": "past"},
    {"t": "place", "v": "store"},
    {"t": "time", "v": "yesterday"}
  ],
  "normalized": "I went to the store yesterday.",
  "phrasal_expansions": [
    "pick up apples",// pick-up and turn-out are phrasal verbs
    "they turned out bad"
  ]
}
Moonwalking

Just like a musician learning to play a musical phrase we embrace the forward-motion of of a literal phrase. The last word is important so thats where we start

Example Drill:  (back‑chain layers)
I went to the store yesterday to pick up some apples but they ended up not being very good.
"good..very good..
not being very good"
"ended up..they ended up"
"not being very good"
"they ended up not being very good."
"but they ended up not being very good"
(continue back to the previous phrases)
"to pick up some apples" "yesterday" and "I went to the store"
ChatsGotYourTongue (Interactive Role‑Play)

With ChatsGotYourTongue, learners step into a text-RPG-style world populated with NPCs (non-player characters) they can actually talk to. Ordering food, checking in at a hotel, or asking for directions becomes a dialogue, not a worksheet. Each NPC interaction feels like a mini role-play that gives the learner agency and makes practice feel more like a game than a lesson.

For people who want to master specific situations we have Groundhog Mode: instead of one long storyline, the learner can loop through everyday situations again and again until they feel confident. Each pass gives them a chance to try new phrases, experiment with different responses, and build fluency through repetition. Unlike a rigid curriculum, it’s not about being stuck in a single loop—it’s about giving the learner control over the pace and path, with the chat offering gentle nudges and suggestions.

Example NPC Dialogue

NPC (Waiter):
“Hello! Welcome. Table for one, or are you waiting for someone?”

  • “Table for one, please.” (Learner must type or speak answers for credit — now or later)
  • “I’m waiting for my friend.”
  • (improvise your own answer) (with context-aware predictive text options)

Example: Learner types "I'm" (Chat suggests: not  just  waiting)

Learner selects "waiting" (Chat suggests: for  to  on)

Learner selects "for" (Chat suggests: the  you  my)

Learner selects "waiting" (Chat suggests: for  to  on)

Learner thinks about these options, knowing that each choice will work grammatically — even if the result isn't what they planned to say.

Learner selects "my" (Chat suggests: friend  family  colleague)

In a traditional text app, this could end up making a strange sentence like I'm waiting for my sister and her husband and my brother and their daughter and I have been working on this since we got here so I'm gonna be going home to take care of the dogs and get some stuff to take home. ChatsGotYourTongue has context and should help you make sense.

However, in Quinglish, the learner is encouraged to embrace the unexpected and not be embarrassed easily. The goal is to get learners talking. Producing perfect sentences will come, but exploring the language freely is "helpful in learning English". Eventually s/he will “say what they mean and mean what they say.”

NPC (Waiter):
“Great. Would you like to sit inside or outside?” (or stares blankly at Learner if they decided to roll with the sister-dog-word-salad)

Learner Response (chosen or improvised):
“Outside, please.”

NPC (Waiter):
“Perfect, follow me. Here’s your menu. Would you like something to drink while you look?”

Scenario Spec

# Airport Bardo (spec excerpt)
{
  "id": "airport-bardo",
  "roles": ["learner", "agent"],
  "vocab_floor": ["passport", "gate", "boarding"],
  "difficulty": 1,
  "loop": "Groundhog‑day style until success criteria met"
}
API / CLI

Document how to call the tokenizer, drills, and scenario engines.

# Example CLI
$ quinglish tokenize --in sample.txt --out tokens.jsonl
$ cgyt run --scenario airport-bardo --user mike
Data Schema (JSONL)

Branch‑aware JSONL seeds for tagging, embeddings, and evaluation.

{"id":"pair-001#s0","role":"user","text":"As a young man…","hashtags":["#BuddyClause","#Ornate"],"meta":{"thread":"abc","ts":"2025-09-10"}}
{"id":"pair-001#r0","role":"assistant","text":"Normalized…","hashtags":["#Basic","#Moonwalk"],"meta":{"model":"gpt"}}
Ciatric (Semantic Brain / Search)

Describe the Semantic Event Bus (#SEB), tagging pipeline, embeddings, and RAG.

  • Voice‑likelihood scorer, completion tagger, accuracy evaluator.
  • Vector DB choices (local‑first), privacy, ownership.
Roadmap
  • MVPs & demo milestones.
  • Data collection ethics (#ConsentPipeline).
  • Open‑source & collaboration invites.
Glossary
  • Buddy‑clause: your compact phrase pair unit.
  • Moonwalk: back‑chaining drill pattern.
  • NPC: non‑player character used for role‑play.
References
  • Add links to papers, prior art, FCC project spec, etc.