Triple

T540039
Position Surface form Disambiguated ID Type / Status
Subject House of Hanover E12609 entity
Predicate namedAfter P63 FINISHED
Object City of Hanover E21642 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: City of Hanover | Statement: [House of Hanover, namedAfter, City of Hanover]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Hanover
Context triple: [House of Hanover, namedAfter, City of Hanover]
  • A. Hanover chosen
    Hanover is a historic city in northern Germany that served as the capital of the former Kingdom of Hanover and the ancestral seat of the British House of Hanover.
  • B. Oldenburg
    Oldenburg is a historic university city in northwestern Germany known for its cultural heritage and role as a regional economic center.
  • C. Mitte, Hanover
    Mitte, Hanover is the central district of the German city of Hanover, encompassing its historic core, main governmental buildings, and key cultural landmarks.
  • D. Lüneburg
    Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
  • E. Braunschweig
    Braunschweig is a historic city in northern Germany known for its medieval architecture, cultural institutions, and role as an important economic and scientific center.
  • 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_69a49334226c81908b0ea1689ef6aa3f completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4985e51908190a34aa82ea9dbee1e completed March 1, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69a566fce9808190931b7c88b5c5686f completed March 2, 2026, 10:31 a.m.
Created at: March 1, 2026, 7:32 p.m.