Triple
T12188923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monthélie AOC |
E290408
|
entity |
| Predicate | grapeCategoryWhite |
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: [Monthélie AOC, grapeCategoryWhite, Chardonnay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grapeCategoryWhite Context triple: [Monthélie AOC, grapeCategoryWhite, Chardonnay]
-
A.
wineVariety
Indicates the specific type or variety of wine associated with an entity.
-
B.
grapeFamily
Indicates that one entity belongs to, or is classified within, the same botanical family as grapes.
-
C.
whiteWineShare
Indicates the proportion or share of white wine within a larger set, such as total wine consumption, production, or sales.
-
D.
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).
-
E.
grapeColorProduced
Indicates the color that is produced by or characteristic of a given grape.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d938cd2edc8190b1971349dbc0dee0 |
completed | April 10, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69d91c38321c819080d500d0d64a04f6 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:50 p.m.