Triple
T12706829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Von-Melle-Park campus |
E303609
|
entity |
| Predicate | locatedInDistrict |
P40
|
FINISHED |
| Object | Hamburg-Eimsbüttel |
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: Hamburg-Eimsbüttel | Statement: [Von-Melle-Park campus, locatedInDistrict, Hamburg-Eimsbüttel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hamburg-Eimsbüttel Context triple: [Von-Melle-Park campus, locatedInDistrict, Hamburg-Eimsbüttel]
-
A.
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.
-
B.
Eimsbüttel
chosen
Eimsbüttel is a borough of Hamburg, Germany, known for its dense urban neighborhoods, green spaces, and well-connected public transport.
-
C.
Hamburg-Nord
Hamburg-Nord is a central borough of the German city-state of Hamburg, comprising several districts and neighborhoods including Fuhlsbüttel.
-
D.
Fuhlsbüttel
Fuhlsbüttel is a district in the northern German city of Hamburg best known for hosting the city’s international airport.
-
E.
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.
- 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9620663e881908d367170ed6d2c81 |
completed | April 10, 2026, 8:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f671b4832c8190abc17f5f33b3552a |
completed | May 2, 2026, 9:50 p.m. |
Created at: April 9, 2026, 5:23 p.m.