Triple
T17988023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sopron wine region |
E430286
|
entity |
| Predicate | hasWineTourism |
P25529
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Sopron wine region, hasWineTourism, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWineTourism Context triple: [Sopron wine region, hasWineTourism, yes]
-
A.
wineTourism
chosen
Indicates a relationship where tourism activities are specifically centered around visiting wine-producing regions, wineries, and related wine experiences.
-
B.
locatedInWineTourismCorridor
Indicates that something is situated within a designated wine tourism corridor or route.
-
C.
hasWinery
Indicates a relationship where a subject owns, operates, or is associated with a particular winery.
-
D.
hasNearbyWinery
Indicates that one entity is located close to, or in the vicinity of, a winery.
-
E.
hasWineRoute
Indicates that there is a designated wine-related route or trail connecting the subject to the object.
- 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b29d3ad4819096c2600aa2a99f21 |
completed | April 19, 2026, 10:46 a.m. |
| PD | Predicate disambiguation | batch_69e3f90039e4819080527f860dca042e |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:23 a.m.