Triple
T27997376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Carniola |
E707048
|
entity |
| Predicate | hasWineSpeciality |
P124558
|
FINISHED |
| Object | Metliška črnina |
—
|
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: Metliška črnina | Statement: [White Carniola, hasWineSpeciality, Metliška črnina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWineSpeciality Context triple: [White Carniola, hasWineSpeciality, Metliška črnina]
-
A.
hasWineCategory
Indicates that one entity is classified under, or associated with, a particular category or type of wine.
-
B.
wineSpeciality
chosen
Indicates that an entity (such as a person, place, or establishment) is particularly known for, focused on, or distinguished by a specific type or aspect of wine.
-
C.
hasWineInstitution
Indicates that an entity is associated with, managed by, or belongs to a specific wine-related institution (such as a winery, wine school, or wine organization).
-
D.
hasSommelier
Indicates that one entity is served, advised, or attended by a sommelier associated with it.
-
E.
hasSparklingWine
Indicates that an entity possesses, includes, or is associated with sparkling 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_69ef96b980d88190a753b2f9a978595a |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f67c9fe7b48190b79b4041357edb49 |
completed | May 2, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69f678cc272081909e5c70f1bc7407f0 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 27, 2026, 7:54 p.m.