Triple

T13919804
Position Surface form Disambiguated ID Type / Status
Subject Barsinghausen E334711 entity
Predicate locatedNear P294 FINISHED
Object 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: Hanover | Statement: [Barsinghausen, locatedNear, Hanover]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanover
Context triple: [Barsinghausen, locatedNear, 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. Hanover
    Hanover is a small town in South Africa, known as the birthplace of prominent trade unionist Zwelinzima Vavi.
  • 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 small suburban town in Plymouth County, Massachusetts, known for its residential character and local businesses south of Boston.
  • E. Hanover
    Hanover is a surname most notably associated with Donna Hanover, an American journalist, actress, and former First Lady of New York City.
  • 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_69d81c5f739081908bc05b2461f54828 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2aa428ac819084e7c4b244d15f20 completed April 14, 2026, 11:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce7c4a788190a1e7619a00ab0c2e completed May 3, 2026, 10:38 p.m.
Created at: April 9, 2026, 10:16 p.m.