Triple
T34818211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Échelle des Crus |
E1003694
|
entity |
| Predicate | AutreCruThresholdRange |
P181517
|
FINISHED |
| Object | 80–89 percent |
—
|
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: 80–89 percent | Statement: [Échelle des Crus, AutreCruThresholdRange, 80–89 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: AutreCruThresholdRange Context triple: [Échelle des Crus, AutreCruThresholdRange, 80–89 percent]
-
A.
hasGrandCru
Indicates that an entity possesses, is associated with, or includes a wine classified as Grand Cru.
-
B.
hasPremierCruClassé
Indicates that an entity holds or is assigned a Premier Cru Classé classification or status.
-
C.
BanyulsGrandCruMinimumAlcohol
Indicates that a Banyuls Grand Cru wine meets or exceeds the specified minimum alcohol content required for that designation.
-
D.
hasWineRange
Indicates that an entity offers, includes, or is associated with a particular selection or range of wines.
-
E.
dominantGrapePercentageRequirement
Indicates the minimum percentage of a single grape variety that must be present in a wine for it to be considered dominant or to meet a specific labeling or classification rule.
- 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_69f76db717088190811b4e744610f37d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77abaa8008190bd81a42b0b0b055f |
completed | May 3, 2026, 4:41 p.m. |
| PD | Predicate disambiguation | batch_69f7795b1abc8190823664d1caa94649 |
completed | May 3, 2026, 4:35 p.m. |
| PDg | Predicate description generation | batch_69f77a39135081908ae22d2a23b44e74 |
completed | May 3, 2026, 4:39 p.m. |
Created at: May 3, 2026, 4 p.m.