Triple

T3678029
Position Surface form Disambiguated ID Type / Status
Subject Mitte, Hanover E78042 entity
Predicate hasPart P35 FINISHED
Object Hanover city centre E260163 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: Hanover city centre | Statement: [Mitte, Hanover, hasPart, Hanover city centre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanover city centre
Context triple: [Mitte, Hanover, hasPart, Hanover city centre]
  • A. Hanover government quarter
    The Hanover government quarter is the central administrative district of Hanover, Germany, housing key state and municipal government buildings and institutions.
  • B. Hanover
    Hanover is a small suburban town in Plymouth County, Massachusetts, known for its residential character and local businesses south of Boston.
  • C. Hanover
    Hanover is a small New Hampshire town best known as the home of Dartmouth College, an Ivy League institution.
  • D. Hanover
    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.
  • E. Hanover, Lower Saxony, Germany chosen
    Hanover, Lower Saxony, Germany is a major northern German city and regional capital known for its trade fairs, cultural institutions, and historical role as a former royal seat.
  • 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_69ad85e18c1c8190be8aafb227f39f48 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc46599188190a046eddb0d85c483 completed March 8, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3a50d40819081aad0c72bcaee9d completed March 14, 2026, 2:10 a.m.
Created at: March 8, 2026, 3:25 p.m.