Triple
T4905345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Army White Service Uniform |
E109900
|
entity |
| Predicate | uniformClass |
P23327
|
FINISHED |
| Object | service 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: service dress | Statement: [Army White Service Uniform, uniformClass, service dress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uniformClass Context triple: [Army White Service Uniform, uniformClass, service dress]
-
A.
uniformStyle
Indicates that the related entities share the same or a consistent style, pattern, or formatting.
-
B.
uniformCategory
chosen
Indicates that two or more entities share the same classification or type within a defined category system.
-
C.
uniformDistinction
Indicates that a clear and consistent difference is maintained between two or more entities within a given context.
-
D.
uniformizedBy
Indicates that one entity has been made uniform, standardized, or brought into a consistent form or structure by another entity.
-
E.
usesUniform
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
- 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_69bd441180708190ba42ffb44fea533a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd706245e48190a61d573438461c30 |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c306b188190a08a7856beb76db4 |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:29 p.m.