Triple

T10290787
Position Surface form Disambiguated ID Type / Status
Subject Binnenalster E241355 entity
Predicate adjacentTo P224 FINISHED
Object Altstadt (Hamburg) 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: Altstadt (Hamburg) | Statement: [Binnenalster, adjacentTo, Altstadt (Hamburg)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Altstadt (Hamburg)
Context triple: [Binnenalster, adjacentTo, Altstadt (Hamburg)]
  • 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. Altstadt (Frankfurt am Main)
    Altstadt (Frankfurt am Main) is the historic old town district of Frankfurt, Germany, known for its reconstructed medieval streets, traditional architecture, and major cultural landmarks.
  • C. Fuhlsbüttel
    Fuhlsbüttel is a district in the northern German city of Hamburg best known for hosting the city’s international airport.
  • D. Brunsbüttel
    Brunsbüttel is a German port town at the western entrance of the Kiel Canal on the North Sea coast of Schleswig-Holstein.
  • 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_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_69d71d1465e88190aaa8b295df3f9c8c completed April 9, 2026, 3:29 a.m.
Created at: April 6, 2026, 11:41 a.m.