Triple
T7737972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cameron Highlanders |
E175430
|
entity |
| Predicate | typeOfUniform |
P4224
|
FINISHED |
| Object | Highland dress |
—
|
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: Highland dress | Statement: [Cameron Highlanders, typeOfUniform, Highland dress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfUniform Context triple: [Cameron Highlanders, typeOfUniform, Highland dress]
-
A.
usesUniform
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
-
B.
variableType
Indicates that one entity is the type or data category of the other entity, which is a variable.
-
C.
typeOfUnit
Indicates that one entity specifies the kind or category of measurement unit that the other entity belongs to.
-
D.
dimensionType
Indicates the specific kind or category of dimension that characterizes how something is measured or structured.
-
E.
typeOf
chosen
Indicates that one entity is a specific kind, class, or category instance of another more general 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_69c6995f9c60819092e386192bd63c6f |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c70402169481909b219dc5f4a64b9b |
completed | March 27, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69c7016c4a748190a7012030edaefcee |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:07 p.m.