Triple
T9749718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhine-Ruhr S-Bahn |
E236408
|
entity |
| Predicate | primaryHub |
P394
|
FINISHED |
| Object | Duisburg Hauptbahnhof |
E236409
|
NE 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: Duisburg Hauptbahnhof | Statement: [Rhine-Ruhr S-Bahn, primaryHub, Duisburg Hauptbahnhof]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Duisburg Hauptbahnhof Context triple: [Rhine-Ruhr S-Bahn, primaryHub, Duisburg Hauptbahnhof]
-
A.
Duisburg Hauptbahnhof
chosen
Duisburg Hauptbahnhof is the central railway station and major transportation hub serving the city of Duisburg in western Germany.
-
B.
Düsseldorf Hauptbahnhof
Düsseldorf Hauptbahnhof is the main railway station of Düsseldorf and a major regional and long-distance transport hub in western Germany.
-
C.
Dortmund Hauptbahnhof
Dortmund Hauptbahnhof is the main railway station and central transportation hub of the city of Dortmund in Germany.
-
D.
Wuppertal Hauptbahnhof
Wuppertal Hauptbahnhof is the main railway station and central transport hub of the city of Wuppertal in western Germany.
-
E.
Darmstadt Hauptbahnhof
Darmstadt Hauptbahnhof is the main railway station and central transportation hub of the city of Darmstadt in the German state of Hesse.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca84d4eddc8190996fec1417d2bae8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f6a2f8c8190a6f6af6587ee90b8 |
completed | April 1, 2026, 10:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc4321cc8190a5197d87ebfe38fb |
completed | April 5, 2026, 2:43 a.m. |
Created at: March 30, 2026, 8:24 p.m.