Triple
T11977845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iris germanica |
E285079
|
entity |
| Predicate | fragrance |
P23045
|
FINISHED |
| Object | often fragrant flowers |
—
|
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: often fragrant flowers | Statement: [Iris germanica, fragrance, often fragrant flowers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fragrance Context triple: [Iris germanica, fragrance, often fragrant flowers]
-
A.
fragranceInspiration
Indicates that one entity serves as the creative or conceptual inspiration behind the fragrance of another entity.
-
B.
hasFragrance
chosen
Indicates that one entity possesses or emits a particular scent or aroma associated with another entity.
-
C.
perfumer
Indicates that an entity creates, blends, or is professionally responsible for producing perfumes or fragrances for another entity or context.
-
D.
scentPositioning
Indicates the spatial placement or arrangement of a scent relative to other objects, locations, or reference points.
-
E.
olfactoryFamily
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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903acbb9081908fe7f8360057785c |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902abca70819098291aa51b593708 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.