Triple
T14627092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bourgogne AOC |
E343376
|
entity |
| Predicate | grapeSourceFlexibility |
P115097
|
FINISHED |
| Object | can blend grapes from different parts of Burgundy |
—
|
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: can blend grapes from different parts of Burgundy | Statement: [Bourgogne AOC, grapeSourceFlexibility, can blend grapes from different parts of Burgundy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grapeSourceFlexibility Context triple: [Bourgogne AOC, grapeSourceFlexibility, can blend grapes from different parts of Burgundy]
-
A.
grapeSource
Indicates that one entity is the origin or provider of grapes used by another entity.
-
B.
grapeCondition
Indicates the state or quality of a grape, such as its health, ripeness, or any notable physical condition.
-
C.
grapeVarietyAllowed
Indicates that a specific grape variety is permitted or authorized for use in a given context, such as a wine, region, or product specification.
-
D.
usesGrapeType
Indicates that one entity employs or incorporates a specific type or variety of grape in its composition, production, or process.
-
E.
grapeMinimum
Indicates the minimum quantity, size, or threshold value associated with grapes in a given context.
- 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb46a4a9081908472b0a542028a7f |
completed | April 14, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69de657359c88190b082e3e9f86fc1d7 |
completed | April 14, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69de716c17cc8190aeb85296abee85a7 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:26 a.m.