Triple
T24428028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lachen-Speyerdorf |
E615913
|
entity |
| Predicate | partOfWineRoute |
P102970
|
FINISHED |
| Object | Deutsche Weinstraße |
—
|
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: Deutsche Weinstraße | Statement: [Lachen-Speyerdorf, partOfWineRoute, Deutsche Weinstraße]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfWineRoute Context triple: [Lachen-Speyerdorf, partOfWineRoute, Deutsche Weinstraße]
-
A.
locatedInWineTourismCorridor
chosen
Indicates that something is situated within a designated wine tourism corridor or route.
-
B.
wineTourism
Indicates a relationship where tourism activities are specifically centered around visiting wine-producing regions, wineries, and related wine experiences.
-
C.
wineRoute
Indicates a route or path specifically associated with wine-related locations or activities, such as vineyards, wineries, or wine tours.
-
D.
passesThroughWineRegion
Indicates that something (such as a route, path, or boundary) traverses or goes through a geographic area recognized as a wine-producing region.
-
E.
hasNearbyWinery
Indicates that one entity is located close to, or in the vicinity of, a winery.
- 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_69e2d7eadb248190a867130fe45f0388 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f296a983d88190904b559694363a19 |
completed | April 29, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69f287cc4fd4819081e93cc638d9512d |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:15 a.m.