Triple
T15808663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magnolia kobus |
E383284
|
entity |
| Predicate | flowerFragrance |
P23045
|
FINISHED |
| Object | fragrant |
—
|
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: fragrant | Statement: [Magnolia kobus, flowerFragrance, fragrant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flowerFragrance Context triple: [Magnolia kobus, flowerFragrance, fragrant]
-
A.
flowerType
Indicates the specific kind or category of flower associated with an entity.
-
B.
fragranceInspiration
Indicates that one entity serves as the creative or conceptual inspiration behind the fragrance of another entity.
-
C.
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.
-
D.
hasFragrance
chosen
Indicates that one entity possesses or emits a particular scent or aroma associated with another entity.
-
E.
floweringUse
Indicates the use or application of something specifically for flowering or promoting the flowering process.
- 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_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b52896bc819086ef95cc63e90daa |
completed | April 16, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69e0053b847c8190945726c3ddac21cc |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:48 a.m.