Triple
T30611891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schloss Vollrads |
E779199
|
entity |
| Predicate | hasWinemakingHistorySince |
P59581
|
FINISHED |
| Object | medieval period |
—
|
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: medieval period | Statement: [Schloss Vollrads, hasWinemakingHistorySince, medieval period]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWinemakingHistorySince Context triple: [Schloss Vollrads, hasWinemakingHistorySince, medieval period]
-
A.
hasWineMakingTradition
chosen
Indicates that a place or group has an established, culturally recognized history and practice of producing wine.
-
B.
hasWinemakingFacility
Indicates that an entity possesses or is associated with a facility where winemaking activities are carried out.
-
C.
producesWine
Indicates that one entity creates or manufactures wine as a product.
-
D.
alsoProducesWineIn
Indicates that the subject, in addition to other products or activities, produces wine in the specified location or context.
-
E.
grapesVinifiedAt
Indicates that grapes were processed and turned into wine at a specific location or facility.
- 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_69f224a21fc08190abd9d8dd9eb6bb4c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6c49627908190b3553474c7c3072b |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
Created at: April 29, 2026, 8:26 p.m.