Triple
T10950660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamburg Airport |
E258716
|
entity |
| Predicate | located in |
P40
|
FINISHED |
| Object | Fuhlsbüttel, Hamburg |
E258718
|
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: Fuhlsbüttel, Hamburg | Statement: [Hamburg Airport, located in, Fuhlsbüttel, Hamburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fuhlsbüttel, Hamburg Context triple: [Hamburg Airport, located in, Fuhlsbüttel, Hamburg]
-
A.
Hamburg-Finkenwerder
Hamburg-Finkenwerder is a district of Hamburg, Germany, known for its historic and ongoing role in shipbuilding and aviation industries along the River Elbe.
-
B.
Fuhlsbüttel
chosen
Fuhlsbüttel is a district in the northern German city of Hamburg best known for hosting the city’s international airport.
-
C.
Brunsbüttel
Brunsbüttel is a German port town at the western entrance of the Kiel Canal on the North Sea coast of Schleswig-Holstein.
-
D.
Ohlsdorf, Hamburg
Ohlsdorf, Hamburg is a northern district of Hamburg, Germany, best known for containing one of the world’s largest rural cemeteries, Ohlsdorf Cemetery.
-
E.
Hamburg
Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
- 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770ed2f1c819081ec58457f57889d |
completed | April 9, 2026, 9:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2d733f7d88190b45df5c155ff5a46 |
completed | April 18, 2026, 12:58 a.m. |
Created at: April 8, 2026, 9:23 p.m.