Triple

T1032019
Position Surface form Disambiguated ID Type / Status
Subject United Nations Volunteers E22273 entity
Predicate headquarteredIn P62 FINISHED
Object Bonn, Germany E23133 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: Bonn, Germany | Statement: [United Nations Volunteers, headquarteredIn, Bonn, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bonn, Germany
Context triple: [United Nations Volunteers, headquarteredIn, Bonn, Germany]
  • A. Bonn chosen
    Bonn is a historic German city on the Rhine River, best known for being the birthplace of Ludwig van Beethoven and the former seat of the federal government before reunification.
  • B. Nassau, Germany
    Nassau, Germany is a historic town on the Lahn River in the state of Rhineland-Palatinate, known as the ancestral seat of the House of Nassau.
  • C. Hamm, Germany
    Hamm is a city in the German state of North Rhine-Westphalia, known as an industrial and transportation hub in the eastern Ruhr area.
  • D. Krefeld, Germany
    Krefeld, Germany is an industrial city in North Rhine-Westphalia known historically for its textile and silk production.
  • E. Schröttinghausen, Germany
    Schröttinghausen is a small locality in Germany best known as the birthplace of influential astronomer Walter Baade.
  • 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_69a493d848848190aed4011b34b2e8d3 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b811916481908c05c2dd5ec802ec completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69ace5485ad48190aa56e6228dc98e19 completed March 8, 2026, 2:56 a.m.
Created at: March 1, 2026, 7:41 p.m.