Triple

T10950002
Position Surface form Disambiguated ID Type / Status
Subject Reeperbahn E258700 entity
Predicate partOf P40 FINISHED
Object Hamburg-Mitte borough E232790 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-Mitte borough | Statement: [Reeperbahn, partOf, Hamburg-Mitte borough]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hamburg-Mitte borough
Context triple: [Reeperbahn, partOf, Hamburg-Mitte borough]
  • A. Hamburg-Mitte chosen
    Hamburg-Mitte is the central borough of Hamburg, Germany, encompassing the historic city center, major commercial areas, and key cultural and political institutions.
  • B. Bahrenfeld district of Hamburg
    The Bahrenfeld district of Hamburg is a western borough of the German city known for its mix of residential areas, sports and event venues, and its association with local football culture.
  • C. Bornheim Mitte
    Bornheim Mitte is a central public transit station in Frankfurt’s Bornheim district, serving as a key stop on the city’s U-Bahn network.
  • 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_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.