README.md

---
license: cc-by-4.0
tags:
  - glyphic
  - symbolic-language
  - semantic-protocol
  - structured-meaning
  - text-to-glyph
  - glyph-to-text
  - agent-cognition
  - dataset
language:
  - en
pretty_name: Glyphic Dataset v1
task_categories:
  - text2text-generation
  - sequence-modeling
size_categories:
  - 10K<n<100K
---
Glyphic Dataset v1

A structured dataset for training language models to understand and generate Glyphic Language — a symbolic protocol designed for drift‑resistant agent cognition.

This dataset contains:

    Text → Glyph mappings

    Glyph → Text mappings

    Structured Meaning representations

    CTX envelope examples (identity, intent, memory, behavior, safety, state, thought)

It is the reference dataset for training Glyphic‑aware LLMs.
Dataset Contents

The dataset includes three primary JSONL files:
1. text_to_glyph.jsonl

Each line contains:
json

{
  "text": "The agent remembers a promise.",
  "glyph": "<G:...>"
}

2. glyph_to_text.jsonl

Each line contains:
json

{
  "glyph": "<G:...>",
  "text": "The agent remembers a promise."
}

3. structured_meaning.jsonl

Each line contains:
json

{
  "text": "The agent remembers a promise.",
  "meaning": {
    "actor": "agent",
    "action": "remember",
    "object": "promise",
    "context": {...}
  },
  "glyph": "<G:...>"
}

These files are generated using the Glyphic Language Toolkit:
Code

https://github.com/GlyphicMind-Solutions/Glyphic-Language

How to Load the Dataset

Using Hugging Face datasets:
python

from datasets import load_dataset

ds = load_dataset("GlyphicMind/glyphic-dataset-v1", split="train")

You can inspect entries:
python

print(ds[0])

Dataset Schema
Text → Glyph

    text: natural language sentence

    glyph: encoded Glyphic sequence

Glyph → Text

    glyph: symbolic sequence

    text: natural language reconstruction

Structured Meaning

    text: natural language

    meaning: structured semantic representation

    glyph: encoded symbolic sequence

The meaning schema is defined in:
Code

glyphic-language/docs/semantic_model.md

Intended Use

This dataset is designed for:

    training LLMs to understand Glyphic

    training LLMs to generate Glyphic

    symbolic reasoning research

    drift‑resistant agent architectures

    CTX‑based identity, intent, memory, and behavior modeling

    protocol‑driven agent communication

It is not a general‑purpose natural language dataset.
How to Train a Glyphic‑Aware Model

A full training pipeline is provided in:
Code

glyphic-language/training/

Typical steps:

    Generate or extend the dataset using:
    Code

    generator/run_generator.py

    Load the dataset with Hugging Face datasets

    Fine‑tune a base model (LLaMA/Mistral/etc.)

    Export as .gguf for inference

    Use Glyphic envelopes at runtime to eliminate drift

A reference model is available at:
Code

GlyphicMind/glyphic-llm-v1

Regenerating or Extending the Dataset

To regenerate or extend this dataset:

    Clone the Glyphic Language Toolkit:
    Code

    https://github.com/GlyphicMind-Solutions/Glyphic-Language

    Modify dictionary entries, templates, or CTX files

    Run the generator:
    bash

    python -m generator.run_generator

    Validate using:
    bash

    python -m interpreter.interpreter --validate

See:

    training/dataset_generation_guide.md

    generator/templates_*

    dictionary/

    syntax/

Why Glyphic Reduces LLM Drift

Glyphic provides:
1. Deterministic structure

Meaning is encoded symbolically, not as free‑form prose.
2. Strict grammar

BNF‑defined syntax prevents ambiguity.
3. CTX protocol

Identity, intent, memory, behavior, safety, and state are explicit fields.
4. Envelope validation

Controllers enforce structure before and after LLM inference.
5. Separation of concerns

The LLM becomes a stateless pattern engine; Glyphic holds the meaning.
License

This dataset is licensed under:

Creative Commons Attribution 4.0 International (CC‑BY 4.0)

You may reuse, modify, and build upon this dataset with attribution.
Citation
Code

Glyphic Dataset v1 (2026). GlyphicMind Solutions.
https://huggingface.co/GlyphicMind/glyphic-dataset-v1