Triple
T26310982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mon Paris Eau de Toilette |
E661818
|
entity |
| Predicate | fragranceType |
P10884
|
FINISHED |
| Object | modern 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: modern chypre | Statement: [Mon Paris Eau de Toilette, fragranceType, modern chypre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fragranceType Context triple: [Mon Paris Eau de Toilette, fragranceType, modern chypre]
-
A.
hasFragrance
Indicates that one entity possesses or emits a particular scent or aroma associated with another entity.
-
B.
fragranceInspiration
Indicates that one entity serves as the creative or conceptual inspiration behind the fragrance of another entity.
-
C.
hasFragranceForm
Indicates that an entity has a specific form or type of fragrance it is associated with or presented in.
-
D.
scentPositioning
Indicates the spatial placement or arrangement of a scent relative to other objects, locations, or reference points.
-
E.
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.
- 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_69ee812dacfc81908484aade9120fba9 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 26, 2026, 10:22 p.m.