Triple
T2522400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolce & Gabbana The One |
E55552
|
entity |
| Predicate | concentration |
P39616
|
FINISHED |
| Object | Eau de Parfum |
—
|
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: Eau de Parfum | Statement: [Dolce & Gabbana The One, concentration, Eau de Parfum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: concentration Context triple: [Dolce & Gabbana The One, concentration, Eau de Parfum]
-
A.
notableStateConcentration
Indicates that a significant portion of the instances or activity of something is concentrated within a particular state or region.
-
B.
salinity
Indicates the concentration of dissolved salts present in or affecting something, typically a body of water or environment.
-
C.
concentratedInCity
Indicates that a large proportion or primary presence of something is located within a particular city.
-
D.
controlled
Indicates that one entity has power, authority, or influence to direct, regulate, or determine the behavior, actions, or state of another entity.
-
E.
consumes
Indicates that one entity eats, drinks, or otherwise uses up another entity as a resource or nourishment.
- 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_69ab49e4749c8190813311efd1630f1b |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd23895348190bb4dad6d7174893a |
completed | March 7, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69abd0c144b0819092f32a13c1d127e5 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd1487e0c8190b90dcf30586ad4cd |
completed | March 7, 2026, 7:18 a.m. |
Created at: March 6, 2026, 9:46 p.m.