Triple
T19926328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ohlsdorf, Hamburg |
E478930
|
entity |
| Predicate | hasNeighbouringQuarter |
P96797
|
FINISHED |
| Object | Fuhlsbüttel |
—
|
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: Fuhlsbüttel | Statement: [Ohlsdorf, Hamburg, hasNeighbouringQuarter, Fuhlsbüttel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fuhlsbüttel Context triple: [Ohlsdorf, Hamburg, hasNeighbouringQuarter, Fuhlsbüttel]
-
A.
Fuhlsbüttel
chosen
Fuhlsbüttel is a district in the northern German city of Hamburg best known for hosting the city’s international airport.
-
B.
Eimsbüttel
Eimsbüttel is a borough of Hamburg, Germany, known for its dense urban neighborhoods, green spaces, and well-connected public transport.
-
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.
Poppenbüttel
Poppenbüttel is a residential quarter in the borough of Wandsbek in Hamburg, Germany, known for its suburban character and green surroundings.
-
E.
Hamburg-Eidelstedt
Hamburg-Eidelstedt is a residential and commercial quarter in the northwestern part of Hamburg, Germany, known for its local rail connections and suburban character.
- 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659ca52c881908dc8053bf61be4c4 |
completed | April 20, 2026, 4:52 p.m. |
Created at: April 10, 2026, 1:53 p.m.