Add WorldWordSemNet dataset card

README.md

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+---
+license: apache-2.0
+language:
+- en
+tags:
+- semantic
+- dictionary
+- wordnet
+- taxonomy
+- nlp
+- training-data
+- knowledge-graph
+- species
+- gbif
+pretty_name: WorldWordSemNet
+size_categories:
+- 1M<n<10M
+---
+
+# 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.
+
+---
+
+## 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
+
+---
+
+## 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.
+
+---
+
+## 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 |
+
+---
+
+## Format
+
+JSONL — one JSON object per line. Example entry:
+
+```json
+{
+  "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"
+  }
+}
+```
+
+---
+
+## 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.
+
+---
+
+## License
+
+Apache 2.0.