Triple
T21675106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cannonau di Sardegna |
E534945
|
entity |
| Predicate | typicalPhenolicContent |
P2069
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Cannonau di Sardegna, typicalPhenolicContent, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPhenolicContent Context triple: [Cannonau di Sardegna, typicalPhenolicContent, high]
-
A.
tanninLevel
chosen
Indicates the degree or intensity of tannins present in or associated with something, typically a beverage like wine or tea.
-
B.
typicalCelluloseContent
Indicates the usual or characteristic amount of cellulose present in or associated with an entity.
-
C.
typicalBlendCabernetFrancPercentage
Indicates the percentage of Cabernet Franc that is typically included in a particular wine blend.
-
D.
hasBitternessLevel
Indicates that an entity is associated with a specific degree or intensity of bitterness.
-
E.
typicalBlendMerlotPercentage
Indicates the usual proportion of Merlot used in a blend relative to the other grape varieties.
- 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_69e0c46898008190aa618a4af55bd1ee |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef8a0ed5388190b8f1932fb3f11c6a |
completed | April 27, 2026, 4:08 p.m. |
| PD | Predicate disambiguation | batch_69e6968abfdc81909cf9e0bd72db9eca |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:41 p.m.