Triple
T139233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Coast AVA |
E2814
|
entity |
| Predicate | typicalVariety |
P5973
|
FINISHED |
| Object | Cabernet Sauvignon |
—
|
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: Cabernet Sauvignon | Statement: [North Coast AVA, typicalVariety, Cabernet Sauvignon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalVariety Context triple: [North Coast AVA, typicalVariety, Cabernet Sauvignon]
-
A.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
B.
parentVariety
Indicates that one variety is the direct parent or source variety from which another variety is derived or developed.
-
C.
typicalProductionType
Indicates the usual or characteristic type of production activity associated with an entity.
-
D.
viewVariesAmong
Indicates that the way something is viewed, perceived, or interpreted differs across multiple entities or contexts.
-
E.
typicalCountryIncluded
Indicates that a country is commonly or characteristically included within a given grouping, context, or set.
- F. None of above. chosen
Provenance (4 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a800148190be119d1d075869b8 |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a2565426c08190aab68e34a6a2d60e |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a25737f9188190b9690dce98aed83a |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.