Triple
T30074402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franconian wine region |
E764277
|
entity |
| Predicate | hasWineTown |
P155152
|
FINISHED |
| Object | Würzburg |
—
|
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: Würzburg | Statement: [Franconian wine region, hasWineTown, Würzburg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWineTown Context triple: [Franconian wine region, hasWineTown, Würzburg]
-
A.
hasWineVillage
chosen
Indicates that a place or region includes or is associated with a village known for wine production or viticulture.
-
B.
hasWinery
Indicates a relationship where a subject owns, operates, or is associated with a particular winery.
-
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.
hasNearbyWinery
Indicates that one entity is located close to, or in the vicinity of, a winery.
-
E.
hasWinemakingFacility
Indicates that an entity possesses or is associated with a facility where winemaking activities are carried out.
- 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_69f22472eee081909791dc372aa766e9 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6b49436b0819094e21603054d05d4 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a5fd8481909433e923c5e24e55 |
completed | May 3, 2026, 2:32 a.m. |
Created at: April 29, 2026, 7:01 p.m.