Triple
T5632380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Idôle |
E147863
|
entity |
| Predicate | bottleAesthetic |
P10886
|
FINISHED |
| Object | rose-gold accents |
—
|
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: rose-gold accents | Statement: [Idôle, bottleAesthetic, rose-gold accents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bottleAesthetic Context triple: [Idôle, bottleAesthetic, rose-gold accents]
-
A.
hasBottleColor
chosen
Indicates that an entity is associated with a bottle characterized by a specific color.
-
B.
drinks
Indicates that one entity consumes a liquid substance, typically by ingesting it through the mouth.
-
C.
signatureDrink
Indicates that a particular drink is the characteristic or specially associated beverage of an entity (such as a person, venue, or brand).
-
D.
madeWithAlcohol
Indicates that something is created, prepared, or produced using alcohol as an ingredient or component.
-
E.
featuresBeverage
Indicates that one entity includes, offers, or presents a particular beverage as part of its contents, services, or characteristics.
- 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_69c00907bc8881909ed760d3ed73ef35 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0225e8e848190a9ccd48fc0d74e5c |
completed | March 22, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69c01b1f12ec8190b4b9d9ee31cabe19 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:40 p.m.