Triple
T11858970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Dior (fragrance) |
E282111
|
entity |
| Predicate | perfumeFamily |
P10884
|
FINISHED |
| Object | chypre |
—
|
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: chypre | Statement: [Miss Dior (fragrance), perfumeFamily, chypre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: perfumeFamily Context triple: [Miss Dior (fragrance), perfumeFamily, chypre]
-
A.
olfactoryFamily
chosen
Indicates a relationship where one entity belongs to, or is categorized within, a particular olfactory family or scent classification defined by the other entity.
-
B.
hasFragrance
Indicates that one entity possesses or emits a particular scent or aroma associated with another entity.
-
C.
fragranceInspiration
Indicates that one entity serves as the creative or conceptual inspiration behind the fragrance of another entity.
-
D.
hasFragranceLine
Indicates that one entity (typically a brand or company) offers or is associated with a particular line or collection of fragrances.
-
E.
perfumer
Indicates that an entity creates, blends, or is professionally responsible for producing perfumes or fragrances for another entity or context.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a69a099c8190a674db64c50eca5a |
completed | April 10, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69d8a2573dbc8190ab432e8e28fde6cc |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.