Triple
T9386464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cérons |
E225916
|
entity |
| Predicate | grapeCondition |
P88645
|
FINISHED |
| Object | often affected by noble rot |
—
|
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: often affected by noble rot | Statement: [Cérons, grapeCondition, often affected by noble rot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grapeCondition Context triple: [Cérons, grapeCondition, often affected by noble rot]
-
A.
grapeMinimum
Indicates the minimum quantity, size, or threshold value associated with grapes in a given context.
-
B.
usesGrapeType
Indicates that one entity employs or incorporates a specific type or variety of grape in its composition, production, or process.
-
C.
grapeSource
Indicates that one entity is the origin or provider of grapes used by another entity.
-
D.
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.
-
E.
hasRegulatedGrapes
Indicates that certain grapes are subject to specific rules, standards, or controls imposed by an authority or regulation.
- 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_69ca842e9dcc8190a264119e683cfe04 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd50d3964c8190b0353f56df755db8 |
completed | April 1, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_69cca53bd6ec81909bf403ce304e5c08 |
completed | April 1, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69cca89b3368819087a3d69270c1f185 |
completed | April 1, 2026, 5:09 a.m. |
Created at: March 30, 2026, 7:45 p.m.