Triple
T29944245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sémillon–Sauvignon Blanc–Muscadelle |
E760588
|
entity |
| Predicate | derivesAromaticNotesFrom |
P152625
|
FINISHED |
| Object | Muscadelle |
—
|
NE NERFINISHED |
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: Muscadelle | Statement: [Sémillon–Sauvignon Blanc–Muscadelle, derivesAromaticNotesFrom, Muscadelle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: derivesAromaticNotesFrom Context triple: [Sémillon–Sauvignon Blanc–Muscadelle, derivesAromaticNotesFrom, Muscadelle]
-
A.
notableFlavorNotes
Indicates that something is characterized by specific, distinguishable flavor notes that are especially prominent or noteworthy.
-
B.
characteristicAroma
chosen
Indicates that one entity has a distinctive smell or scent that characterizes or is typically associated with another entity.
-
C.
secondaryAroma
Indicates that an entity has a secondary or supporting aroma characteristic in addition to its primary scent.
-
D.
aromaticOilsPresent
Indicates that aromatic oils are present in or associated with the specified entity or context.
-
E.
leafAromaCompound
Indicates that a particular aroma compound is present in, derived from, or characteristically associated with a plant’s leaves.
- 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_69f22463f3648190a603c3ff305c660b |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6a916d2e08190bafc01cba73b6469 |
completed | May 3, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69f6a7548eb48190a69b60a3c6ad53b9 |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 29, 2026, 6:23 p.m.