Triple
T12191778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eidelstedt station |
E290480
|
entity |
| Predicate | locatedInAdministrativeTerritory |
P40
|
FINISHED |
| Object | Eimsbüttel borough |
E970294
|
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: Eimsbüttel borough | Statement: [Eidelstedt station, locatedInAdministrativeTerritory, Eimsbüttel borough]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eimsbüttel borough Context triple: [Eidelstedt station, locatedInAdministrativeTerritory, Eimsbüttel borough]
-
A.
Eimsbüttel
chosen
Eimsbüttel is a borough of Hamburg, Germany, known for its dense urban neighborhoods, green spaces, and well-connected public transport.
-
B.
Fuhlsbüttel
Fuhlsbüttel is a district in the northern German city of Hamburg best known for hosting the city’s international airport.
-
C.
Poppenbüttel
Poppenbüttel is a residential quarter in the borough of Wandsbek in Hamburg, Germany, known for its suburban character and green surroundings.
-
D.
Brunsbüttel
Brunsbüttel is a German port town at the western entrance of the Kiel Canal on the North Sea coast of Schleswig-Holstein.
-
E.
Friedrichswerder district
Friedrichswerder district is a historic quarter in central Berlin, Germany, known for its 19th-century architecture and cultural landmarks.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91c54a4648190ad0f84c229534155 |
completed | April 10, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63ee694848190a1362934110b6ceb |
completed | May 2, 2026, 6:13 p.m. |
Created at: April 8, 2026, 9:50 p.m.