Dontopedia

Probability Values

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

Probability Values has 8 facts recorded in Dontopedia across 3 references, with 2 live disagreements.

8 facts·4 predicates·3 sources·2 in dispute

Mostly:rdf:type(3), has member(3), sum(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (4)

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.

representsRepresents(2)

containsContains(1)

orderedMatchingOrdered Matching(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:typeProbability List[1]
Rdf:typeFloat Collection[2]
Rdf:typeProbability Distribution[3]
Has Member0.1[1]
Has Member0.2[1]
Has Member0.3[1]
Sum0.6[1]
Individual Probabilitiestrue[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/a3a5d835-1848-42bd-98e5-0660dbb98a7f
ex:ProbabilityList
hasMemberbeam/a3a5d835-1848-42bd-98e5-0660dbb98a7f
0.1
hasMemberbeam/a3a5d835-1848-42bd-98e5-0660dbb98a7f
0.2
hasMemberbeam/a3a5d835-1848-42bd-98e5-0660dbb98a7f
0.3
sumbeam/a3a5d835-1848-42bd-98e5-0660dbb98a7f
0.6
individualProbabilitiesbeam/a3a5d835-1848-42bd-98e5-0660dbb98a7f
true
typebeam/f360e0ec-4b02-47fa-98bb-438a47e7b5f0
ex:FloatCollection
typebeam/34ffcd35-801a-4acf-b1f5-659bb6c98a27
ex:ProbabilityDistribution

References (3)

3 references
  1. ctx:claims/beam/a3a5d835-1848-42bd-98e5-0660dbb98a7f
    • full textbeam-chunk
      text/plain1 KBdoc:beam/a3a5d835-1848-42bd-98e5-0660dbb98a7f
      Show excerpt
      [Turn 1631] Assistant: Certainly! Creating a risk assessment model in Python is a great way to quantify and manage potential cost risks. Below is an enhanced version of your initial code, which includes additional steps to help you map cost
  2. ctx:claims/beam/f360e0ec-4b02-47fa-98bb-438a47e7b5f0
    • full textbeam-chunk
      text/plain1 KBdoc:beam/f360e0ec-4b02-47fa-98bb-438a47e7b5f0
      Show excerpt
      2. **Simulate Risk Occurrence**: Determine which risks occur based on their probabilities. 3. **Calculate Risk Score**: Compute the overall risk score by combining the probabilities and impacts of the occurring risks. ### Example Python Co
  3. ctx:claims/beam/34ffcd35-801a-4acf-b1f5-659bb6c98a27
    • full textbeam-chunk
      text/plain1 KBdoc:beam/34ffcd35-801a-4acf-b1f5-659bb6c98a27
      Show excerpt
      def update_weights(engine1_accuracy, engine2_accuracy): total_accuracy = engine1_accuracy + engine2_accuracy if total_accuracy == 0: return (0.5, 0.5) # Default equal weights if both accuracies are zero new_weights = (e

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