Dontopedia

Context Components

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)

Context Components has 34 facts recorded in Dontopedia across 7 references, with 6 live disagreements.

34 facts·10 predicates·7 sources·6 in dispute

Mostly:has member(8), rdf:type(5), has component(5)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (17)

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.

isComponentOfIs Component of(4)

isMemberOfIs Member of(4)

requiresRequires(2)

definesDefines(1)

hasComponentHas Component(1)

hasPartHas Part(1)

involvesIdentificationInvolves Identification(1)

producesProduces(1)

suggestedContextComponentsSuggested Context Components(1)

usesUses(1)

Other facts (31)

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.

31 facts
PredicateValueRef
Has MemberUser History[3]
Has MemberCurrent Query[3]
Has MemberSystem State[3]
Has MemberExternal Data Sources[3]
Has MemberUser History[5]
Has MemberCurrent Query[5]
Has MemberSystem State[5]
Has MemberExternal Data Sources[5]
Rdf:typeConcept[2]
Rdf:typeContext Structure[4]
Rdf:typeContext Collection[5]
Rdf:typeCollection[6]
Rdf:typeData Structure[7]
Has ComponentInitial Weights[2]
Has ComponentUser History[5]
Has ComponentCurrent Query[5]
Has ComponentSystem State[5]
Has ComponentExternal Data Sources[5]
IncludesUser History[3]
IncludesCurrent Query[3]
IncludesSystem State[3]
IncludesExternal Data Sources[3]
ContainsUser History[5]
ContainsCurrent Query[5]
ContainsSystem State[5]
ContainsExternal Data Sources[5]
Listed AsBullet Points[1]
Produced byStep 1[3]
Requires WeightsWeight Assignment[3]
Has Number of Members4[5]
ConstitutesFull Context[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.

listedAsbeam/c0dac4b7-a8bf-4fc4-b8c0-172938ac7e75
ex:bullet-points
typebeam/5da37977-83e8-48be-bdd8-808083c26ac7
ex:Concept
labelbeam/5da37977-83e8-48be-bdd8-808083c26ac7
Context Components
hasComponentbeam/5da37977-83e8-48be-bdd8-808083c26ac7
ex:initial-weights
includesbeam/a71afa78-3ac4-4931-987f-ad0a5b6a3f57
ex:user-history
includesbeam/a71afa78-3ac4-4931-987f-ad0a5b6a3f57
ex:current-query
includesbeam/a71afa78-3ac4-4931-987f-ad0a5b6a3f57
ex:system-state
includesbeam/a71afa78-3ac4-4931-987f-ad0a5b6a3f57
ex:external-data-sources
labelbeam/a71afa78-3ac4-4931-987f-ad0a5b6a3f57
Context Components
hasMemberbeam/a71afa78-3ac4-4931-987f-ad0a5b6a3f57
ex:user-history
hasMemberbeam/a71afa78-3ac4-4931-987f-ad0a5b6a3f57
ex:current-query
hasMemberbeam/a71afa78-3ac4-4931-987f-ad0a5b6a3f57
ex:system-state
hasMemberbeam/a71afa78-3ac4-4931-987f-ad0a5b6a3f57
ex:external-data-sources
producedBybeam/a71afa78-3ac4-4931-987f-ad0a5b6a3f57
ex:step-1
requiresWeightsbeam/a71afa78-3ac4-4931-987f-ad0a5b6a3f57
ex:weight-assignment
typebeam/3f4c4caf-7cac-4379-9d6d-0d4735a709bb
ex:ContextStructure
hasMemberbeam/17359c4f-ce82-472f-b0cd-20671ade934f
ex:user-history
hasMemberbeam/17359c4f-ce82-472f-b0cd-20671ade934f
ex:current-query
hasMemberbeam/17359c4f-ce82-472f-b0cd-20671ade934f
ex:system-state
hasMemberbeam/17359c4f-ce82-472f-b0cd-20671ade934f
ex:external-data-sources
typebeam/17359c4f-ce82-472f-b0cd-20671ade934f
ex:ContextCollection
hasNumberOfMembersbeam/17359c4f-ce82-472f-b0cd-20671ade934f
4
constitutesbeam/17359c4f-ce82-472f-b0cd-20671ade934f
ex:full-context
containsbeam/17359c4f-ce82-472f-b0cd-20671ade934f
ex:user-history
containsbeam/17359c4f-ce82-472f-b0cd-20671ade934f
ex:current-query
containsbeam/17359c4f-ce82-472f-b0cd-20671ade934f
ex:system-state
containsbeam/17359c4f-ce82-472f-b0cd-20671ade934f
ex:external-data-sources
hasComponentbeam/17359c4f-ce82-472f-b0cd-20671ade934f
ex:user-history
hasComponentbeam/17359c4f-ce82-472f-b0cd-20671ade934f
ex:current-query
hasComponentbeam/17359c4f-ce82-472f-b0cd-20671ade934f
ex:system-state
hasComponentbeam/17359c4f-ce82-472f-b0cd-20671ade934f
ex:external-data-sources
typebeam/8c53f93c-330d-4b71-9b2a-a7c521b5200c
ex:Collection
labelbeam/8c53f93c-330d-4b71-9b2a-a7c521b5200c
context components
typebeam/11402421-e0dd-4257-81f5-18735667d931
ex:Data-Structure

References (7)

7 references
  1. ctx:claims/beam/c0dac4b7-a8bf-4fc4-b8c0-172938ac7e75
    • full textbeam-chunk
      text/plain1 KBdoc:beam/c0dac4b7-a8bf-4fc4-b8c0-172938ac7e75
      Show excerpt
      [Turn 10470] User: I'm trying to optimize the intent precision of my LLM prompts, and I've been experimenting with different context weights. Currently, I'm achieving 88% intent precision on 2,500 test queries, but I want to improve it furt
  2. ctx:claims/beam/5da37977-83e8-48be-bdd8-808083c26ac7
  3. ctx:claims/beam/a71afa78-3ac4-4931-987f-ad0a5b6a3f57
    • full textbeam-chunk
      text/plain1 KBdoc:beam/a71afa78-3ac4-4931-987f-ad0a5b6a3f57
      Show excerpt
      Identify the different components of your context and assign initial weights. For example: - `user_history` - `current_query` - `system_state` - `external_data_sources` ### Step 2: Generate Weight Combinations Use a systematic approach t
  4. ctx:claims/beam/3f4c4caf-7cac-4379-9d6d-0d4735a709bb
    • full textbeam-chunk
      text/plain1 KBdoc:beam/3f4c4caf-7cac-4379-9d6d-0d4735a709bb
      Show excerpt
      # Output the best combination of weights print(f"Best Intent Precision: {best_precision}") print(f"Best Weights: {best_weights}") ``` ### Explanation 1. **Define Context Components and Initial Weights**: Identify the components of your co
  5. ctx:claims/beam/17359c4f-ce82-472f-b0cd-20671ade934f
    • full textbeam-chunk
      text/plain1 KBdoc:beam/17359c4f-ce82-472f-b0cd-20671ade934f
      Show excerpt
      ``` Replace the placeholder functions with your actual logic to evaluate the intent precision. Would you like to proceed with these steps or do you have any specific questions about any part of the process? [Turn 10474] User: Sure, let's
  6. ctx:claims/beam/8c53f93c-330d-4b71-9b2a-a7c521b5200c
    • full textbeam-chunk
      text/plain1 KBdoc:beam/8c53f93c-330d-4b71-9b2a-a7c521b5200c
      Show excerpt
      # Evaluate the precision precision = evaluate_intent_precision(normalized_weights, test_queries) # Track the best combination if precision > best_precision: best_precision = precision best_weights = norm
  7. ctx:claims/beam/11402421-e0dd-4257-81f5-18735667d931
    • full textbeam-chunk
      text/plain1 KBdoc:beam/11402421-e0dd-4257-81f5-18735667d931
      Show excerpt
      2. **Refine the Search**: If the initial search does not yield significant improvements, consider narrowing down the range or using more sophisticated optimization techniques. 3. **Validate Results**: Validate the results on a separate vali

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