Triple

T10290766
Position Surface form Disambiguated ID Type / Status
Subject Binnenalster E241355 entity
Predicate locatedIn P40 FINISHED
Object Hamburg-Mitte 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 | Statement: [Binnenalster, locatedIn, Hamburg-Mitte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hamburg-Mitte
Context triple: [Binnenalster, locatedIn, Hamburg-Mitte]
  • 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. 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.
  • C. Fuhlsbüttel
    Fuhlsbüttel is a district in the northern German city of Hamburg best known for hosting the city’s international airport.
  • D. 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.
  • E. Hanover-Mitte
    Hanover-Mitte is the central district of Hanover, Germany, encompassing the city’s historic core, main commercial areas, and key transport hubs.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2d281348190bac00cf826689cd7 completed April 7, 2026, 9:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f85dcbac8190a2ac66354010e328 completed April 9, 2026, 12:52 a.m.
Created at: April 6, 2026, 11:41 a.m.