Triple

T10950729
Position Surface form Disambiguated ID Type / Status
Subject Fuhlsbüttel E258718 entity
Predicate locatedIn P40 FINISHED
Object Northern Hamburg E7419 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: Northern Hamburg | Statement: [Fuhlsbüttel, locatedIn, Northern Hamburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Northern Hamburg
Context triple: [Fuhlsbüttel, locatedIn, Northern Hamburg]
  • A. Hamburg metropolitan region
    The Hamburg metropolitan region is a major economic and population center in northern Germany, anchored by the city of Hamburg and its extensive port and logistics industries.
  • B. Norderstedt
    Norderstedt is a city in northern Germany that forms part of the Hamburg metropolitan area and is one of the larger urban centers in the state of Schleswig-Holstein.
  • C. Hamburg and Lübeck
    Hamburg and Lübeck is a diocese of the Evangelical Lutheran Church in Northern Germany that encompasses the historic Hanseatic cities of Hamburg and Lübeck and their surrounding regions.
  • D. Hamburg chosen
    Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
  • E. Hamburg-Finkenwerder, Germany
    Hamburg-Finkenwerder, Germany is an industrial district of Hamburg best known for its large Airbus manufacturing and assembly facilities.
  • 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_69e23c57038c819087671177c2ed5633 completed April 17, 2026, 1:57 p.m.
Created at: April 8, 2026, 9:23 p.m.