Triple
T9826527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rully |
E238667
|
entity |
| Predicate | primaryGrapeVarietyWhite |
P975
|
FINISHED |
| Object | Chardonnay |
—
|
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: Chardonnay | Statement: [Rully, primaryGrapeVarietyWhite, Chardonnay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryGrapeVarietyWhite Context triple: [Rully, primaryGrapeVarietyWhite, Chardonnay]
-
A.
primaryGrapeVariety
chosen
Indicates that one entity is the main or predominant grape variety used in producing the other entity (typically a wine or wine-based product).
-
B.
traditionalGrapeVariety
Indicates that a grape variety is traditionally or historically used in a specific region, wine style, or cultural winemaking practice.
-
C.
primaryGrapeUse
Indicates that a grape variety is primarily used for a particular purpose, such as winemaking, table consumption, or raisin production.
-
D.
primaryWhiteVariety
Indicates that one entity is the primary white (light-skinned or white-colored) variety or form of another entity.
-
E.
synonymOfPrimaryGrape
Indicates that one grape variety is a synonym or alternate name for the primary grape variety specified.
- 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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb32370e8819087c85fb8328587be |
completed | April 2, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cd03e01ea881909a7d93fc3994ace5 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:32 p.m.