Triple
T24566400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sercial |
E607800
|
entity |
| Predicate | wineLabelIndication |
P156372
|
FINISHED |
| Object | Sercial on Madeira labels indicates driest style |
—
|
NE NERFINISHED |
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: Sercial on Madeira labels indicates driest style | Statement: [Sercial, wineLabelIndication, Sercial on Madeira labels indicates driest style]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineLabelIndication Context triple: [Sercial, wineLabelIndication, Sercial on Madeira labels indicates driest style]
-
A.
wineName
Indicates the specific name or designation assigned to a wine.
-
B.
wineStructure
Indicates the overall sensory framework of a wine, encompassing how its components like acidity, tannin, body, and alcohol are balanced and interact.
-
C.
wineAlcoholPotential
Indicates the potential alcohol content that a wine could reach based on its current sugar level or fermentation stage.
-
D.
wineQualityLevelProduced
Indicates the quality level or grade assigned to the wine that is produced in the described production event or process.
-
E.
redWinesLabeledAs
Indicates that certain red wines are designated or identified by a particular label or labeling term.
- 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_69e2c4cc35a48190990b7571bc086df8 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a92082a881908896dcdda85559b9 |
completed | April 30, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
| PDg | Predicate description generation | batch_69f2a846c5bc81909ba50cee483bea91 |
completed | April 30, 2026, 12:54 a.m. |
Created at: April 18, 2026, 2:28 a.m.