Triple

T5961027
Position Surface form Disambiguated ID Type / Status
Subject Alter Zoll E132635 entity
Predicate near P350 FINISHED
Object Bonn city centre 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 city centre | Statement: [Alter Zoll, near, Bonn city centre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bonn city centre
Context triple: [Alter Zoll, near, Bonn city centre]
  • 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. Museum Mile Bonn
    Museum Mile Bonn is a cultural district in Bonn, Germany, known for its dense concentration of major museums and art institutions along a short stretch of the city.
  • C. Cologne
    Cologne is a historic German city on the Rhine River, renowned for its Gothic cathedral, vibrant cultural scene, and status as a major economic and media hub.
  • D. Bonn UN Campus station
    Bonn UN Campus station is a light rail and train stop in Bonn, Germany, serving the United Nations campus and nearby conference and government facilities.
  • E. Frankfurt skyline
    The Frankfurt skyline is a distinctive cityscape dominated by modern high-rise towers and skyscrapers that form one of Europe’s most prominent financial and architectural hubs.
  • 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_69c0086c2364819091e9fe2f58fa2517 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c039fd6dd48190a6020bef38b1be82 completed March 22, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3e8f234819099336503a797e55b completed March 23, 2026, 6:55 a.m.
Created at: March 22, 2026, 4:02 p.m.