Triple
T24198932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kolitzheim |
E599914
|
entity |
| Predicate | localWineType |
P42321
|
FINISHED |
| Object | Franconian wine |
—
|
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: Franconian wine | Statement: [Kolitzheim, localWineType, Franconian wine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: localWineType Context triple: [Kolitzheim, localWineType, Franconian wine]
-
A.
wineCategory
chosen
Indicates the classification or type of wine that an entity (such as a specific wine) belongs to.
-
B.
wineStyle
Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
-
C.
regulatesWineType
Indicates that one entity has authority or influence over the rules, standards, or conditions governing a particular type of wine.
-
D.
wineTypeAllowed
Indicates that a particular type of wine is permitted or acceptable in a given context or for a given purpose.
-
E.
wineVariety
Indicates the specific type or variety of wine associated with an entity.
- 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_69e288ceaab88190899d0acb5931591d |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9f61f881909f7e1287388ff982 |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c43e55688190b55fc20274ed471c |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:36 p.m.