Triple
T2735459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Côte de Beaune-Villages AOC |
E60619
|
entity |
| Predicate | labeling |
P19697
|
FINISHED |
| Object | may be labeled without specific village name |
—
|
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: may be labeled without specific village name | Statement: [Côte de Beaune-Villages AOC, labeling, may be labeled without specific village name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: labeling Context triple: [Côte de Beaune-Villages AOC, labeling, may be labeled without specific village name]
-
A.
labelOf
Indicates that one entity serves as the name, tag, or identifying label assigned to another entity.
-
B.
labelCatalog
Indicates assigning or associating a descriptive label or identifier with a catalog entity or catalog entry.
-
C.
ownedLabel
Indicates that a label is possessed or controlled by a particular owner or entity.
-
D.
usedLabel
chosen
Indicates that one entity has applied, assigned, or referenced a particular label to another entity or resource.
-
E.
nativeLabel
Indicates the label or name of an entity expressed in its own native or original language.
- 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_69ab4b77febc819095603eb012cd141b |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb1022488190af84e536946b2e37 |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd82859348190bce3be8f2e9d60ba |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:56 p.m.