Triple
T15527594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ribera del Duero DO |
E369121
|
entity |
| Predicate | minimumTempranilloContentForReds |
P119034
|
FINISHED |
| Object | 75% |
—
|
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: 75% | Statement: [Ribera del Duero DO, minimumTempranilloContentForReds, 75%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minimumTempranilloContentForReds Context triple: [Ribera del Duero DO, minimumTempranilloContentForReds, 75%]
-
A.
minimumAlcoholRed
Indicates that there is a specified minimum alcohol content requirement associated with red wine or red alcoholic beverages.
-
B.
minimumMalbecPercentage
Indicates the minimum required percentage of Malbec in a composition, blend, or product for a given rule or classification to apply.
-
C.
grapeMinimum
Indicates the minimum quantity, size, or threshold value associated with grapes in a given context.
-
D.
redWineRequired
Indicates that red wine is needed or mandated in the given context or situation.
-
E.
typicalRedBlendProfile
Indicates that something exhibits the characteristic flavor, aroma, and structural profile commonly associated with a standard red wine 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0414620588190958ffde651ccab5f |
completed | April 16, 2026, 1:54 a.m. |
| PD | Predicate disambiguation | batch_69ded28ab0588190a47a9090d1238707 |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded57165288190979b7acb71ad5145 |
completed | April 15, 2026, 12:01 a.m. |
Created at: April 10, 2026, 4:05 a.m.