Triple
T27085500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muscat de Beaumes-de-Venise |
E686024
|
entity |
| Predicate | grapeGrowingClimate |
P40401
|
FINISHED |
| Object | Mediterranean |
—
|
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: Mediterranean | Statement: [Muscat de Beaumes-de-Venise, grapeGrowingClimate, Mediterranean]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grapeGrowingClimate Context triple: [Muscat de Beaumes-de-Venise, grapeGrowingClimate, Mediterranean]
-
A.
viticulturalClimate
chosen
Indicates the type of climate conditions relevant to grape growing and wine production that characterize a given region or area.
-
B.
grapeGrowingLatitudeRange
Indicates the range of latitudes within which grapes are typically grown or suitable for cultivation.
-
C.
grapeGrowingInfluence
Indicates how various factors affect or shape the process and outcomes of growing grapes.
-
D.
grapeCondition
Indicates the state or quality of a grape, such as its health, ripeness, or any notable physical condition.
-
E.
grapePlantingShare
Indicates the proportion or share of grape planting activity attributed to or carried out by a particular entity relative to a larger whole.
- 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_69ef148940ec819097b5c20fbfbf7c81 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f62345517c819082ca0c9f67792e67 |
completed | May 2, 2026, 4:16 p.m. |
| PD | Predicate disambiguation | batch_69f620e0b37481909a280574decbd443 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 8:37 a.m.