Triple
T33515501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L'Esprit de Chevalier (red) |
E858354
|
entity |
| Predicate | drinkingWindowCharacteristic |
P177059
|
FINISHED |
| Object | approachable in youth |
—
|
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: approachable in youth | Statement: [L'Esprit de Chevalier (red), drinkingWindowCharacteristic, approachable in youth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drinkingWindowCharacteristic Context triple: [L'Esprit de Chevalier (red), drinkingWindowCharacteristic, approachable in youth]
-
A.
drinkingWindowStyle
Indicates the typical period or style of time frame during which something (such as a beverage) is considered best suited to be consumed.
-
B.
drinkingPermitted
Indicates that consuming alcoholic beverages is allowed in a given context, location, or situation.
-
C.
drinkWindow
Indicates the time period during which a beverage (typically wine) is considered to be at its best for drinking.
-
D.
drinkingContext
Indicates the situational or environmental circumstances under which a drinking event occurs (such as time, place, social setting, or purpose).
-
E.
drinkingHabit
Indicates an entity’s typical pattern or frequency of consuming alcoholic or other beverages.
- 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_69f3497721848190978fbee5e0a526f8 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f85bfba48190aba95b40642a8ca7 |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f6619404819084662aef1238261c |
completed | May 3, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69f6f814fcf48190ae4504154d1b2c05 |
completed | May 3, 2026, 7:24 a.m. |
Created at: May 1, 2026, 1:39 a.m.