Dontopedia

val dataset

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)

val dataset has 9 facts recorded in Dontopedia across 5 references, with 1 live disagreement.

9 facts·7 predicates·5 sources·1 in dispute

Mostly:rdf:type(2), has bytes(1), derived from(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (6)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

createdForCreated for(1)

hasPartHas Part(1)

rdf:typeRdf:type(1)

usedForUsed for(1)

usesUses(1)

usesDatasetUses Dataset(1)

Other facts (8)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

8 facts
PredicateValueRef
Rdf:typeValidation Data[2]
Rdf:typeDataset[4]
Has Bytes6459383[1]
Derived FromTokenized Dataset[2]
Assigned toeval_dataset[2]
Has Example Count3000[3]
Image Count5000[4]
SynonymValidation Set[5]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

hasBytesblah/watt-activation/part-420
6459383
derivedFrombeam/88c90684-e902-4bc6-a2dd-f749dde78552
ex:tokenized-dataset
typebeam/88c90684-e902-4bc6-a2dd-f749dde78552
ex:ValidationData
assignedTobeam/88c90684-e902-4bc6-a2dd-f749dde78552
eval_dataset
hasExampleCountblah/watt-activation/168
3000
typeblah/watt-activation/251
ex:Dataset
labelblah/watt-activation/251
val dataset
imageCountblah/watt-activation/251
5000
synonymbeam/cc1315f0-7954-44ad-96b4-19d6a2409d50
ex:validation-set

References (5)

5 references
  1. [1]Part 4201 fact
    ctx:discord/blah/watt-activation/part-420
  2. ctx:claims/beam/88c90684-e902-4bc6-a2dd-f749dde78552
    • full textbeam-chunk
      text/plain1 KBdoc:beam/88c90684-e902-4bc6-a2dd-f749dde78552
      Show excerpt
      args=training_args, train_dataset=tokenized_dataset["train"], eval_dataset=tokenized_dataset["validation"] ) # Train the model trainer.train() ``` #### 3. Self-Hosted Model Deployment ##### Environment Setup - **Hardware**:
  3. [3]1681 fact
    ctx:discord/blah/watt-activation/168
    • full textwatt-activation-168
      text/plain3 KBdoc:agent/watt-activation-168/73ee12a6-c466-46d0-8fcc-aeb7b6f8614e
      Show excerpt
      [2026-03-09 19:32] xenonfun: ``` [train] Tokenizing 186,015 examples... 20,000/186,015 (4,496,870 tokens) 40,000/186,015 (8,960,555 tokens) 60,000/186,015 (13,450,804 tokens) 80,000/186,015 (17,894,743 tokens) 100,000/186,015
  4. [4]2513 facts
    ctx:discord/blah/watt-activation/251
    • full textwatt-activation-251
      text/plain1 KBdoc:agent/watt-activation-251/0d79165d-ca43-48df-b924-6b76b157d1a5
      Show excerpt
      [2026-03-12 13:11] xenonfun: ✅ Phase 0 confirmed working — r_global rises monotonically from 0.07 → 0.96 across 16 steps on the production multimodal checkpoint. The architecture supports iterative generation. This is the green light to p
  5. ctx:claims/beam/cc1315f0-7954-44ad-96b4-19d6a2409d50
    • full textbeam-chunk
      text/plain933 Bdoc:beam/cc1315f0-7954-44ad-96b4-19d6a2409d50
      Show excerpt
      - Added an extra linear layer (`fc3`) to increase the depth of the model, allowing it to capture more complex patterns in the data. 4. **Weight Decay (L2 Regularization)**: - Included weight decay in the `optim.Adam` optimizer with a

See also

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