Triple
T9826541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rully |
E238667
|
entity |
| Predicate | typicalAromaWhite |
P71397
|
FINISHED |
| Object | citrus fruit notes |
—
|
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: citrus fruit notes | Statement: [Rully, typicalAromaWhite, citrus fruit notes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAromaWhite Context triple: [Rully, typicalAromaWhite, citrus fruit notes]
-
A.
typicalOakAroma
Indicates that something has the characteristic smell commonly associated with oak wood or oak aging.
-
B.
primaryAroma
Indicates the main or most dominant scent associated with an entity, distinguishing it from secondary or background aromas.
-
C.
wineCharacteristic
Indicates a descriptive property or quality attributed to a wine, such as its flavor, aroma, color, or style.
-
D.
secondaryAroma
chosen
Indicates that an entity has a secondary or supporting aroma characteristic in addition to its primary scent.
-
E.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
- 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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb32370e8819087c85fb8328587be |
completed | April 2, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cd03e01ea881909a7d93fc3994ace5 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:32 p.m.