Triple
T30694533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Page Corps |
E781419
|
entity |
| Predicate | hadUniformType |
P2930
|
FINISHED |
| Object | court dress uniform |
—
|
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: court dress uniform | Statement: [Page Corps, hadUniformType, court dress uniform]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadUniformType Context triple: [Page Corps, hadUniformType, court dress uniform]
-
A.
includesUniformType
Indicates that one entity contains or encompasses a specific type of uniform within its scope or composition.
-
B.
isUniform
Indicates that all elements or parts within a given set, structure, or context share the same characteristics or value.
-
C.
areUniform
Indicates that all elements in a given set or collection share the same value, property, or characteristic.
-
D.
woreUniformOf
Indicates that one entity was dressed in or used the official uniform associated with another entity (such as an organization, group, or role).
-
E.
usesUniform
chosen
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_69f224ab24e08190991d6edb6df58e8b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68bda88048190bdd6992094c7644d |
completed | May 2, 2026, 11:42 p.m. |
| PD | Predicate disambiguation | batch_69f6861170d08190bb98be609d436f84 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:33 p.m.