Triple
T10308652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grover Zampa Vineyards |
E241828
|
entity |
| Predicate | hasVineyardType |
P93295
|
FINISHED |
| Object | estate vineyard |
—
|
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: estate vineyard | Statement: [Grover Zampa Vineyards, hasVineyardType, estate vineyard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVineyardType Context triple: [Grover Zampa Vineyards, hasVineyardType, estate vineyard]
-
A.
hasWineryType
Indicates the specific category or classification of winery associated with an entity.
-
B.
hasVineyards
Indicates that one entity possesses, contains, or is associated with vineyards used for growing grapevines.
-
C.
hasWinery
Indicates a relationship where a subject owns, operates, or is associated with a particular winery.
-
D.
viticulturalAreaType
Indicates the specific type or classification of a viticultural area associated with an entity.
-
E.
hasWinemakingFacility
Indicates that an entity possesses or is associated with a facility where winemaking activities are carried out.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f4f354819080b4ed4bc61bdff6 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d7cada7881908beba55a1dc9ecb9 |
completed | April 7, 2026, 10:09 a.m. |
Created at: April 6, 2026, 11:47 a.m.