ULTRAData/ULTRA.Elite.Semantic.Data.SEMNET

WorldWordSemNet

WorldWordSemNet is a comprehensive English semantic dictionary dataset mapping 3,981,469 words to a structured hierarchy of 286 semantic family classes, built as a training substrate for next-generation language models.

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What's in it

Every entry contains:

• word — the English word or multi-word expression (including scientific species names)
• id — a hierarchical numeric semantic address (e.g. 4.2.8.319) encoding the word's position in the semantic tree
• family — the semantic family label (e.g. ENTITY.ANIMAL.CANINE, ACTION.COMMUNICATION.SPEAK_VERB, DESCRIPTOR.SIZE)
• definitions — dictionary definitions where every token in every definition is also mapped to its own semantic ID — giving a fully grounded semantic graph of language
• taxonomy — for biological entities: full Linnaean taxonomy (kingdom → phylum → class → order → family → genus → rank → scientificName) for 2,791,312 species
• species_description — up to 3 natural-language descriptions per species (202,745 species covered), with every token also semantically mapped

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Semantic Hierarchy

The 286 semantic families are organized into a deep hierarchy:

ENTITY
  ENTITY.ANIMAL
    ENTITY.ANIMAL.CANINE
    ENTITY.ANIMAL.FELINE
    ENTITY.ANIMAL.PRIMATE
    ...
  ENTITY.PLANT
  ENTITY.SUBSTANCE
    ENTITY.SUBSTANCE.CHEMICAL
    ENTITY.SUBSTANCE.FOOD
    ...
  ENTITY.PERSON
  ENTITY.DISEASE
ACTION
  ACTION.COMMUNICATION.SPEAK_VERB
  ACTION.MOVE
  ...
DESCRIPTOR
RELATION
TIME
PLACE
...

Numeric IDs encode the hierarchy directly: 4.2.8.319 means top-level class 4 → subclass 2 → subclass 8 → word 319. Arithmetic operations on IDs are semantically meaningful.

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Scale

Metric	Count
Total words / entries	3,981,469
Words with definitions	773,952
Words with full taxonomy	2,791,312
Species with descriptions	202,745
Semantic families	286
File size (JSONL)	~1.65 GB

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Format

JSONL — one JSON object per line. Example entry:

{
  "word": "dog",
  "id": "4.2.8.319",
  "family": "ENTITY.ANIMAL.CANINE",
  "definitions": [
    {
      "gloss": "A mammal of the family Canidae:",
      "tokens": [
        ["a", "6.3.1"],
        ["mammal", "4.2.23.4481"],
        ["of", "1.5.2.2875"],
        ["the", "6.3.379"],
        ["family", "4.12.6.4773"],
        ["canidae", "4.2.8.113"]
      ]
    }
  ],
  "taxonomy": {
    "kingdom": "Animalia",
    "phylum": "Chordata",
    "class": "Mammalia",
    "order": "Carnivora",
    "family": "Canidae",
    "genus": "Canis",
    "rank": "species"
  }
}

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Intended Use

This dataset was originally built as the semantic substrate for INFINITY — a novel AI architecture that does not use transformers. INFINITY uses sparse directed matrices and a two-layer semantic tether mechanism, trained entirely on hierarchical numeric IDs rather than token embeddings. It is a fundamentally new approach to generative language modeling.

WorldWordSemNet should also serve as a major kickstart for transformer-based models. The combination of:

1. Full semantic family labeling for nearly 4 million words
2. Hierarchically structured numeric IDs that encode meaning arithmetically
3. Definition tokens pre-mapped to their own semantic IDs — a fully grounded semantic graph
4. Complete species taxonomy and biological descriptions integrated at the word level

...makes this dataset uniquely suited for training models that require deep semantic grounding beyond simple statistical co-occurrence.

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License

Apache 2.0.