Triple
T24130103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heidelberger Platz station |
E597923
|
entity |
| Predicate | isInterchangeStationWith |
P98214
|
FINISHED |
| Object | Berlin U-Bahn |
—
|
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: Berlin U-Bahn | Statement: [Heidelberger Platz station, isInterchangeStationWith, Berlin U-Bahn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInterchangeStationWith Context triple: [Heidelberger Platz station, isInterchangeStationWith, Berlin U-Bahn]
-
A.
hasInterchangeStationWith
chosen
Indicates that two transportation lines, routes, or systems share a station where passengers can transfer between them.
-
B.
hasRailInterchangeFunction
Indicates that something serves as a location or facility where rail lines connect or intersect, allowing passengers or goods to transfer between them.
-
C.
interchangeStation
Indicates a station where passengers can transfer between different routes, lines, or modes of transportation.
-
D.
isRailwayStation
Indicates that the subject is a railway station, i.e., a facility where trains regularly stop to pick up or drop off passengers and/or freight.
-
E.
isPassengerStationFor
Indicates that a station serves as a boarding and alighting point for passengers on a particular transportation line or service.
- 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_69e288c808b881909fed7d18f04bcbbe |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1df7644808190b4bbbf4db1539f48 |
completed | April 29, 2026, 10:37 a.m. |
| PD | Predicate disambiguation | batch_69f1765650fc8190a6bc1eb512b240bf |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:24 p.m.