Triple
T5869936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago Bliss |
E130488
|
entity |
| Predicate | primaryUniformType |
P28113
|
FINISHED |
| Object | minimal equipment uniforms |
—
|
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: minimal equipment uniforms | Statement: [Chicago Bliss, primaryUniformType, minimal equipment uniforms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryUniformType Context triple: [Chicago Bliss, primaryUniformType, minimal equipment uniforms]
-
A.
primaryUniformAssociation
Indicates that one entity is designated as the main or primary uniform associated with another entity.
-
B.
usesUniform
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
-
C.
primaryType
chosen
Indicates the main or most fundamental category or classification assigned to an entity, distinguishing it from any secondary or auxiliary types.
-
D.
uniformStyle
Indicates that the related entities share the same or a consistent style, pattern, or formatting.
-
E.
uniformCategory
Indicates that two or more entities share the same classification or type within a defined category system.
- 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_69c0085047dc8190af24e311edad3c07 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ffaef081909faaa7f420a3b9b7 |
completed | March 22, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69c03347e51c81909053bcf34e3b88ab |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:56 p.m.