Triple
T31202118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greco di Tufo wine |
E795502
|
entity |
| Predicate | maximumOtherGrapesContent |
P183129
|
FINISHED |
| Object | 15% |
—
|
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: 15% | Statement: [Greco di Tufo wine, maximumOtherGrapesContent, 15%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumOtherGrapesContent Context triple: [Greco di Tufo wine, maximumOtherGrapesContent, 15%]
-
A.
alsoUsesGrapeVariety
Indicates that one entity, in addition to another, makes use of the same grape variety in its composition or production.
-
B.
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.
-
C.
grapeVarietal
Indicates that one entity is a specific type or variety of grape used in wine or grape production in relation to another entity.
-
D.
primaryGrapeVariety
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.
maximumViognierPercentage
Indicates the highest allowable proportion of Viognier in a given wine or blend.
- 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_69f224d8c6608190b7882466521f62be |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f798387ea481909f51303f53a22e52 |
completed | May 3, 2026, 6:47 p.m. |
| PD | Predicate disambiguation | batch_69f7961550f88190b7bb8a9155458b54 |
completed | May 3, 2026, 6:38 p.m. |
| PDg | Predicate description generation | batch_69f79798663481908d6bc48dd6a94ca6 |
completed | May 3, 2026, 6:44 p.m. |
Created at: April 29, 2026, 9:09 p.m.