Triple
T27149625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Elks American Viticultural Area |
E682348
|
entity |
| Predicate | hasWineries |
P6791
|
FINISHED |
| Object | small wineries |
—
|
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: small wineries | Statement: [West Elks American Viticultural Area, hasWineries, small wineries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWineries Context triple: [West Elks American Viticultural Area, hasWineries, small wineries]
-
A.
hasWinery
chosen
Indicates a relationship where a subject owns, operates, or is associated with a particular winery.
-
B.
hasNearbyWinery
Indicates that one entity is located close to, or in the vicinity of, a winery.
-
C.
hasWineInstitution
Indicates that an entity is associated with, managed by, or belongs to a specific wine-related institution (such as a winery, wine school, or wine organization).
-
D.
hasWinemakingFacility
Indicates that an entity possesses or is associated with a facility where winemaking activities are carried out.
-
E.
hasVineyards
Indicates that one entity possesses, contains, or is associated with vineyards used for growing grapevines.
- 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_69eefaceb2a08190b9659b7f730629f5 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f65876c52c8190bc889c7a67bd07f3 |
completed | May 2, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69f6575d89788190aca478e4aea05a65 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 27, 2026, 9:13 a.m.