Kamelo: A Rule-Based Constructed Language for Universal, Logical Communication
Introduction
Natural languages are messy, ambiguous, and often inefficient for transmitting structured ideas. Kamelo is a proposal for a constructed language designed to address these issues by building words from logical, compositional units. This post outlines the foundations of Kamelo—a rule-based, expandable language using fixed character sets and hierarchical categories to represent meaning with minimal ambiguity or memorization.
Kamelo is not intended to replace natural languages but rather to serve as a meta-language: a bridge for logical communication between humans, AIs, and across cultures, especially in low-bandwidth or assistive contexts. This proposal is relevant to LessWrong’s audience as it touches on rationality, AI alignment, and communication efficiency.
Motivation and Design Goals
Logical Construction: Every word is built from layered semantic categories—no arbitrary mappings.
No Memory Dependence: You can understand a word’s meaning by parsing its parts, not memorizing vocabulary.
Minimal Ambiguity: Sentence-level communication inherits meaning clearly from word-level rules.
Scalable: Works for both common and rare concepts using multi-level, logical trees.
Human-AI Symbiosis: Useful in alignment protocols, translation layers, or accessible UI design.
Core Mechanics of Kamelo
Alphabet Fixed 5-symbol phoneme set: ka, me, lo, ti, su (All words are built from these like a base-5 prefix tree)
Word Structure (Example: “apple”)
| Level | Encodes | Example Segment |
|---|---|---|
| L1 | Word type | ka = Noun |
| L2 | Noun subtype | ka = Proper noun |
| L3 | Domain | su = Species |
| L4 | Biological class | me = Plant |
| L5 | Subclass | ti = Fruit |
| L6–L8 | Meaning specificity | su-ka-ka-me (apple) |
Each level is chosen from a tree of categories with 5 branches per level. More common distinctions appear earlier (shorter words).
Encoding Example: Apple
ka → Noun
ka → Proper Noun
su → Species
me → Plant
ti → Fruit
su → Family: Rosaceae
ka → Sweet taste
ka → Crunchy texture
me → Tree-grown Resulting Kamelo word: kakasu meti susukakakakame
This structure is entirely self-descriptive if you know the rules.
Use Cases
Assistive Tech: Minimal phoneme-based speech for those with limited mobility.
AI Protocols: Alignment communication using rule-parsed, auditable intent structures.
Low-bandwidth communication: Works well over noise-prone audio or radio.
Cross-cultural linguistics: Universal base allows logical translation.
Counterpoints & Limitations
It is difficult to read with long repeated segments (e.g.,
kakakaka).Requires learning category trees (though this could be made visual, like emoji-based cues).
Expressiveness is limited until the category trees are fully developed.
No flexibility for poetic or metaphorical meaning—by design.
Future Work
Visual builders or translators to make Kamelo usable.
Mapping natural languages → Kamelo + vice versa.
Define sentence structure (LaMelo?) for higher-order communication.
Why I’m Posting on LessWrong
Kamelo is a rational attempt to reduce ambiguity in human language. It touches on:
AI alignment and protocol robustness
Meta-rationality in language design
Assistive tech and communication efficiency
I’m publishing this to invite critique, collaboration, and exploration into whether Kamelo can be a useful construct—not just for theory, but for real-world protocols and tools.
Call for Feedback
I’d love to hear thoughts on:
Logical completeness of the system
Known linguistic/cognitive objections
Whether this is useful for human-AI alignment
How to bootstrap a usable dictionary/encoder
I love a good conlang. This one feels like an interesting start, though I’ll be upfront and say I don’t think this is a bottleneck on anything AI related.
Some thoughts and questions, in no particular order:
“Here’s how words are made” is a start. What’s the grammar like? I think that’s where a lot of ambiguity creeps in to language.
Am I allowed to stop an encoding partway? For instance, am I allowed to say
kakasu meti suto just mean noun, it’s a fruiting plant in the Rosaceae family, or do I have to keep going to be grammatically correct?I kind of like the idea of a tree structure that gets more specific as you go. Five phonemes seems too few though- I like what you’re doing with the consonant/vowel setup, but extra options seem very useful for compactness and there’s more options.
Related- do you mind doing the IPA for the phonemes? I’m curious whether for instance “ti” is pronounced like “tired” (tɑɪəd) or like “tin” (tɪn) or “me” is pronounced like “meet” (mit) or “met” (mɛt)
How do pronouns work?
It’s reasonable not to have answers for these yet, I don’t know what stage of conlang creation you’re on.
Hey, Thanks so much for diving into Kamelo, you’ve nailed exactly the kind of questions I’m wrestling with.
Grammar & Ambiguity
You’re totally right — grammar is where ambiguity really enters. Right now, Kamelo doesn’t have a fixed grammar yet. But the idea is:
Word order is generally SVO (subject-verb-object), like English.
Modifiers (adjectives, adverbs) follow what they modify.
Punctuation-like tokens may act as “semantic closers” to end a branch of a conceptual tree.
Stopping Mid-Structure
Yes! You can stop mid-encoding. That’s a key principle: Kamelo is compressible based on shared context, like how we say “the fruit” instead of “a Rosaceae angiosperm of genus Malus”. The idea is to transmit enough meaning for the moment, and go deeper if needed.
That’s why a base like
kakasu meti su(“noun, fruiting plant, [Rosaceae]”)
could be totally valid in conversation, and even shorten further in high-context.
Phoneme Clarification (IPA)
This is still flexible, but currently considering:
The goal is max distinctiveness across modalities — so these sounds are spread in mouth shape, tongue placement, and timing (good for speech-to-sign or tactile mapping later).
Pronouns
Pronouns aren’t fixed “words” like in English. Instead, they act like references. For example:
ka→ “living entity”Then you can say
loafter that in the same convo to refer back to that entity.So something like:
ka ti= “the dog”lo me= “it is happy”(Assuming me = happy or emotive state)
They behave more like pointing mechanisms in programming, and are scope-bound to context.
Final Thoughts
You’re spot on: 5 syllables is limiting — Kamelo is intentionally extreme, like a design provocation. It pushes me to see how much abstraction and compression can be done before the system collapses. Future iterations might have 12–20 syllables for balance.
How would a language like this survive a change in ontology? You take a category and split it into 5 subcategories. What if two years later you find out that a sixth subcategory exists?
If you update the language, you would have to rewrite all existing texts. The problem would not be that they contain archaic words—it would be that all the words are still used, but now they mean something different.
Seemingly similar words (prepending one syllable to a long word or a sentence) will result in a wildly different meaning.
Reminds me of Solresol, except being a 5-tree makes it so it could fit a pentatonic scale, which is fun.
Yesss! Solresol is definitely a spiritual cousin — and you’re right, the pentatonic scale connection is super interesting.
Kamelo using 5 phonemes intentionally echoes both:
the pentatonic musical scale (so it could be spoken, signed, or played as music),
and tree-based semantic logic, where each level refines the concept more.
Solresol mapped syllables to meanings too, but Kamelo’s twist is:
Tree depth encodes specificity.
Context compression is built-in (like pronouns or omitted branches).
Designed from the start to be machine-readable, signable, musical, and tactile.
So theoretically:
A blind person could feel a string of raised tactile glyphs.
A deaf person could see it signed.
A device could parse and translate it.
And a musician could sing meaning.
Is there a way to learn this language? I imagine it would be much more difficult for beginners to have to understand an arbitrary tree structure than individual words
Yes, It is more difficult to understand arbitrary tree structure but the goal is make the tree more and more logical and less and less arbitrary, we need a perfectly logical tree that could describe every meaning (if possible) or atleast as close as possible. When its more logical it’ll be easier to learn and hard to master.