Triple
T17440708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgstraße |
E424141
|
entity |
| Predicate | hasNearbyTransportNode |
P25143
|
FINISHED |
| Object | Hanover Hauptbahnhof |
—
|
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: Hanover Hauptbahnhof | Statement: [Georgstraße, hasNearbyTransportNode, Hanover Hauptbahnhof]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hanover Hauptbahnhof Context triple: [Georgstraße, hasNearbyTransportNode, Hanover Hauptbahnhof]
-
A.
Hannover Hauptbahnhof
chosen
Hannover Hauptbahnhof is the main central railway station of Hanover, Germany, serving as a major national and international transport hub.
-
B.
Hamm Hauptbahnhof
Hamm Hauptbahnhof is the central railway station and major rail hub serving the city of Hamm in North Rhine-Westphalia, Germany.
-
C.
Hagen Hauptbahnhof
Hagen Hauptbahnhof is the main railway station and central transport hub of the city of Hagen in North Rhine-Westphalia, Germany.
-
D.
Braunschweig Hauptbahnhof
Braunschweig Hauptbahnhof is the main railway station and central transportation hub of the city of Braunschweig in Lower Saxony, Germany.
-
E.
Hamburg Central Station
Hamburg Central Station is the main railway hub of Hamburg and one of Germany’s busiest train stations, serving as a key national and international transport interchange.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889d88b6081908bada047f5b3ba51 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44ff75538819083f77756d39a1aaa |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 5:46 a.m.