Triple
T112520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Canadian Air Force |
E2277
|
entity |
| Predicate | uniformColour |
P60
|
FINISHED |
| Object | air force blue |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: air force blue | Statement: [Royal Canadian Air Force, uniformColour, air force blue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uniformColour Context triple: [Royal Canadian Air Force, uniformColour, air force blue]
-
A.
colors
chosen
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
B.
uniformDistinction
Indicates that a clear and consistent difference is maintained between two or more entities within a given context.
-
C.
usesUniform
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
-
D.
typicalBlendStyle
Indicates the usual or characteristic way in which two or more elements are combined or mixed together.
-
E.
numberOfStripes
Indicates the count of distinct stripe markings associated with an entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a256425a488190959d71e39e699d90 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.