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.
Mostly:has member(8), rdf:type(5), has component(5)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound 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)
- Current Query
ex:current-query - External Data Sources
ex:external-data-sources - System State
ex:system-state - User History
ex:user-history
isMemberOfIs Member of(4)
- Current Query
ex:current-query - External Data Sources
ex:external-data-sources - System State
ex:system-state - User History
ex:user-history
definesDefines(1)
- Step 1
ex:step-1
hasComponentHas Component(1)
- Context Weight Combinations
ex:context-weight-combinations
hasPartHas Part(1)
- Step 1
ex:step-1
involvesIdentificationInvolves Identification(1)
- Step 1
ex:step-1
producesProduces(1)
- Step 1
ex:step-1
suggestedContextComponentsSuggested Context Components(1)
- Assistant
ex:assistant
usesUses(1)
- Step 2
ex:step-2
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.
| Predicate | Value | Ref |
|---|---|---|
| Has Member | User History | [3] |
| Has Member | Current Query | [3] |
| Has Member | System State | [3] |
| Has Member | External Data Sources | [3] |
| Has Member | User History | [5] |
| Has Member | Current Query | [5] |
| Has Member | System State | [5] |
| Has Member | External Data Sources | [5] |
| Rdf:type | Concept | [2] |
| Rdf:type | Context Structure | [4] |
| Rdf:type | Context Collection | [5] |
| Rdf:type | Collection | [6] |
| Rdf:type | Data Structure | [7] |
| Has Component | Initial Weights | [2] |
| Has Component | User History | [5] |
| Has Component | Current Query | [5] |
| Has Component | System State | [5] |
| Has Component | External Data Sources | [5] |
| Includes | User History | [3] |
| Includes | Current Query | [3] |
| Includes | System State | [3] |
| Includes | External Data Sources | [3] |
| Contains | User History | [5] |
| Contains | Current Query | [5] |
| Contains | System State | [5] |
| Contains | External Data Sources | [5] |
| Listed As | Bullet Points | [1] |
| Produced by | Step 1 | [3] |
| Requires Weights | Weight Assignment | [3] |
| Has Number of Members | 4 | [5] |
| Constitutes | Full 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.
References (7)
ctx:claims/beam/c0dac4b7-a8bf-4fc4-b8c0-172938ac7e75- full textbeam-chunktext/plain1 KB
doc:beam/c0dac4b7-a8bf-4fc4-b8c0-172938ac7e75Show 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…
ctx:claims/beam/5da37977-83e8-48be-bdd8-808083c26ac7ctx:claims/beam/a71afa78-3ac4-4931-987f-ad0a5b6a3f57- full textbeam-chunktext/plain1 KB
doc:beam/a71afa78-3ac4-4931-987f-ad0a5b6a3f57Show 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…
ctx:claims/beam/3f4c4caf-7cac-4379-9d6d-0d4735a709bb- full textbeam-chunktext/plain1 KB
doc:beam/3f4c4caf-7cac-4379-9d6d-0d4735a709bbShow 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…
ctx:claims/beam/17359c4f-ce82-472f-b0cd-20671ade934f- full textbeam-chunktext/plain1 KB
doc:beam/17359c4f-ce82-472f-b0cd-20671ade934fShow 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…
ctx:claims/beam/8c53f93c-330d-4b71-9b2a-a7c521b5200c- full textbeam-chunktext/plain1 KB
doc:beam/8c53f93c-330d-4b71-9b2a-a7c521b5200cShow 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…
ctx:claims/beam/11402421-e0dd-4257-81f5-18735667d931- full textbeam-chunktext/plain1 KB
doc:beam/11402421-e0dd-4257-81f5-18735667d931Show 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…
See also
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