Triple
T12144933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winterthur |
E289292
|
entity |
| Predicate | railwayStationRank |
P103205
|
FINISHED |
| Object | one of the busiest railway stations in Switzerland |
—
|
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: one of the busiest railway stations in Switzerland | Statement: [Winterthur, railwayStationRank, one of the busiest railway stations in Switzerland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayStationRank Context triple: [Winterthur, railwayStationRank, one of the busiest railway stations in Switzerland]
-
A.
railwayStationCategory
Indicates the classification or type category assigned to a railway station within a rail network or system.
-
B.
hasRailwayStationRole
Indicates that an entity holds or is assigned a specific functional role or capacity within the operation or management of a railway station.
-
C.
hasRailwayStation
Indicates that a place or location is served by, or contains, a railway station.
-
D.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
E.
railwayStationFunction
Indicates that an entity serves as a railway station and specifies the role or function it performs within the railway network.
- F. None of above. chosen
Provenance (4 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915d7109481908bf5fe512bba3c89 |
completed | April 10, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69d9150c18148190bf8152189c0e5fca |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d915d58ab881908b5b7901990308a4 |
completed | April 10, 2026, 3:23 p.m. |
Created at: April 8, 2026, 9:49 p.m.