Triple
T13230468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paderborn |
E315002
|
entity |
| Predicate | hasRailwayStation |
P918
|
FINISHED |
| Object |
Paderborn Hauptbahnhof
Paderborn Hauptbahnhof is the main railway station and central transport hub serving the city of Paderborn in Germany.
|
E1028965
|
NE FINISHED |
How this triple was built (4 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: Paderborn Hauptbahnhof | Statement: [Paderborn, hasRailwayStation, Paderborn Hauptbahnhof]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paderborn Hauptbahnhof Context triple: [Paderborn, hasRailwayStation, Paderborn Hauptbahnhof]
-
A.
Bielefeld Hauptbahnhof
Bielefeld Hauptbahnhof is the main railway station and central transportation hub of the city of Bielefeld in Germany.
-
B.
Osnabrück Hauptbahnhof
Osnabrück Hauptbahnhof is the main railway station and central transport hub of the city of Osnabrück in Lower Saxony, Germany.
-
C.
Bochum Hauptbahnhof
Bochum Hauptbahnhof is the main railway station and central transportation hub of the city of Bochum in Germany.
-
D.
Dortmund Hauptbahnhof
Dortmund Hauptbahnhof is the main railway station and central transportation hub of the city of Dortmund in Germany.
-
E.
Hagen Hauptbahnhof
Hagen Hauptbahnhof is the main railway station and central transport hub of the city of Hagen in North Rhine-Westphalia, Germany.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Paderborn Hauptbahnhof Triple: [Paderborn, hasRailwayStation, Paderborn Hauptbahnhof]
Generated description
Paderborn Hauptbahnhof is the main railway station and central transport hub serving the city of Paderborn in Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Paderborn Hauptbahnhof Target entity description: Paderborn Hauptbahnhof is the main railway station and central transport hub serving the city of Paderborn in Germany.
-
A.
Bielefeld Hauptbahnhof
Bielefeld Hauptbahnhof is the main railway station and central transportation hub of the city of Bielefeld in Germany.
-
B.
Osnabrück Hauptbahnhof
Osnabrück Hauptbahnhof is the main railway station and central transport hub of the city of Osnabrück in Lower Saxony, Germany.
-
C.
Bochum Hauptbahnhof
Bochum Hauptbahnhof is the main railway station and central transportation hub of the city of Bochum in Germany.
-
D.
Dortmund Hauptbahnhof
Dortmund Hauptbahnhof is the main railway station and central transportation hub of the city of Dortmund in Germany.
-
E.
Hagen Hauptbahnhof
Hagen Hauptbahnhof is the main railway station and central transport hub of the city of Hagen in North Rhine-Westphalia, Germany.
- F. None of above. chosen
Provenance (5 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d336ae08190bfc118cfbefddf84 |
completed | April 10, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff2c07488190ad07c544cca63a7d |
completed | May 3, 2026, 7:54 a.m. |
| NEDg | Description generation | batch_69f70408b2088190989c3b38a5d66495 |
completed | May 3, 2026, 8:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f70518acc0819089a987abfd42f928 |
completed | May 3, 2026, 8:19 a.m. |
Created at: April 9, 2026, 9:21 p.m.