Dontopedia

Prompts List

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-05.)

Prompts List has 8 facts recorded in Dontopedia across 1 reference.

8 facts·8 predicates·1 sources

Mostly:rdf:type(1), assigned to(1), has element(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (2)

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.

containsContains(1)

sameLengthAsSame Length As(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:typeList[1]
Assigned toPrompts[1]
Has ElementWrite a short story about a character who visits the capital of France.[1]
Has Length8000[1]
CommentList of prompts for story generation[1]
Unusedtrue[1]
Has Identical Elementstrue[1]
Not Used byParallel Process Queries Function[1]

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.

typebeam/6882a527-957e-49db-80d4-43ff95f419fc
ex:List
assignedTobeam/6882a527-957e-49db-80d4-43ff95f419fc
ex:prompts
hasElementbeam/6882a527-957e-49db-80d4-43ff95f419fc
Write a short story about a character who visits the capital of France.
hasLengthbeam/6882a527-957e-49db-80d4-43ff95f419fc
8000
commentbeam/6882a527-957e-49db-80d4-43ff95f419fc
List of prompts for story generation
unusedbeam/6882a527-957e-49db-80d4-43ff95f419fc
true
hasIdenticalElementsbeam/6882a527-957e-49db-80d4-43ff95f419fc
true
notUsedBybeam/6882a527-957e-49db-80d4-43ff95f419fc
ex:parallel-process-queries-function

References (1)

1 references
  1. ctx:claims/beam/6882a527-957e-49db-80d4-43ff95f419fc
    • full textbeam-chunk
      text/plain1 KBdoc:beam/6882a527-957e-49db-80d4-43ff95f419fc
      Show excerpt
      response = self.tokenizer.decode(outputs[0], skip_special_tokens=True) return response # Initialize the layers retrieval_layer = RetrievalLayer() generation_layer = GenerationLayer() # Function to process a batch of queri

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