Triple
T35656411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nizza DOCG |
E1030297
|
entity |
| Predicate | grapeYieldPolicy |
P32569
|
FINISHED |
| Object | low maximum yields |
—
|
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: low maximum yields | Statement: [Nizza DOCG, grapeYieldPolicy, low maximum yields]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grapeYieldPolicy Context triple: [Nizza DOCG, grapeYieldPolicy, low maximum yields]
-
A.
grapeCondition
Indicates the state or quality of a grape, such as its health, ripeness, or any notable physical condition.
-
B.
yieldPotential
chosen
Indicates the expected amount or capacity of output, production, or benefit that something can generate under given conditions.
-
C.
grapeSourceFlexibility
Indicates that the source or origin of grapes involved in a relationship or process can vary or be chosen flexibly rather than being fixed.
-
D.
usesGrapeType
Indicates that one entity employs or incorporates a specific type or variety of grape in its composition, production, or process.
-
E.
grapePlantingShare
Indicates the proportion or share of grape planting activity attributed to or carried out by a particular entity relative to a larger whole.
- 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_69f76e0938088190a8f199631e97dec3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79f78111c8190b0b8a109c3101da0 |
completed | May 3, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69f79e4d885881908a3612e2e75cf84f |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:05 p.m.