Triple
T12870075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mango Man |
E307824
|
entity |
| Predicate | usesModelsType |
P107384
|
FINISHED |
| Object | top fashion models |
—
|
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: top fashion models | Statement: [Mango Man, usesModelsType, top fashion models]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesModelsType Context triple: [Mango Man, usesModelsType, top fashion models]
-
A.
useOfModel
Indicates that one entity employs, applies, or relies on a particular model for a specific purpose or task.
-
B.
usedByModel
Indicates that something (such as a resource, method, or component) is utilized or consumed by a particular model.
-
C.
usedToModel
Indicates that one entity serves as a model or representation for another entity, typically for purposes of analysis, simulation, or understanding.
-
D.
isModelOf
Indicates that one entity serves as a representation or abstraction that captures the structure or behavior of another entity.
-
E.
usesProductionModel
Indicates that one entity employs or relies on another entity as its primary or official production model in practice.
- F. None of above. chosen
Provenance (4 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97c7f91d08190aac2f6419d3ba992 |
completed | April 10, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69d96fa55b888190ab1612e93c41aec4 |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d97c7d0598819080cab0a2314bc106 |
completed | April 10, 2026, 10:41 p.m. |
Created at: April 9, 2026, 5:38 p.m.