Triple
T19748848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamburg Towers |
E474321
|
entity |
| Predicate | basedIn |
P40
|
FINISHED |
| Object | Hamburg, Germany |
—
|
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: Hamburg, Germany | Statement: [Hamburg Towers, basedIn, Hamburg, Germany]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hamburg, Germany Context triple: [Hamburg Towers, basedIn, Hamburg, Germany]
-
A.
Hamburg-Finkenwerder, Germany
Hamburg-Finkenwerder, Germany is an industrial district of Hamburg best known for its large Airbus manufacturing and assembly facilities.
-
B.
Hamburg
chosen
Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
-
C.
Hamm, Germany
Hamm is a city in the German state of North Rhine-Westphalia, known as an industrial and transportation hub in the eastern Ruhr area.
-
D.
Lüneburg, Germany
Lüneburg, Germany is a historic Hanseatic town in Lower Saxony known for its medieval architecture, former salt trade wealth, and well-preserved old town.
-
E.
Brunswick, Germany
Brunswick, Germany is a historic city in Lower Saxony known for its medieval architecture, former status as a ducal residence, and role as an important commercial and cultural center in northern Germany.
- 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65296fa80819085aa4a18153531cf |
completed | April 20, 2026, 4:21 p.m. |
Created at: April 10, 2026, 1:47 p.m.