Triple
T28658434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reugny, Indre-et-Loire, France |
E725395
|
entity |
| Predicate | belongsToWineArea |
P110198
|
FINISHED |
| Object | Vouvray vineyard area |
—
|
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: Vouvray vineyard area | Statement: [Reugny, Indre-et-Loire, France, belongsToWineArea, Vouvray vineyard area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToWineArea Context triple: [Reugny, Indre-et-Loire, France, belongsToWineArea, Vouvray vineyard area]
-
A.
wineLawRegionName
Indicates that a specific name refers to the legal wine-producing region defined by wine regulations.
-
B.
wineLawRegionType
Indicates the type or category of legal designation that governs wine production in a particular region.
-
C.
belongsToAppellation
chosen
Indicates that something is associated with or falls under a specific appellation or designated name/category.
-
D.
isInWineOrBeerRegion
Indicates that something is located within a geographic area known for producing wine or beer.
-
E.
wineLawRegionFocus
Indicates that a legal rule or regulation specifically concerns or targets a particular geographic region in the context of wine.
- F. None of above.
Provenance (3 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_69f01d84f5f0819087ab5e6143b14ed7 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
Created at: April 28, 2026, 4:56 a.m.