Triple

T19598097
Position Surface form Disambiguated ID Type / Status
Subject Federal Office for Agriculture and Food E470399 entity
Predicate headquartersLocation P62 FINISHED
Object Bonn NE NERFINISHED

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 | Statement: [Federal Office for Agriculture and Food, headquartersLocation, Bonn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bonn
Context triple: [Federal Office for Agriculture and Food, headquartersLocation, Bonn]
  • 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. Cologne
    Cologne is an unincorporated community within Galloway Township in Atlantic County, New Jersey, known primarily as a small residential area in the region.
  • 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. Düsseldorf
    Düsseldorf is a major German city on the Rhine River known for its fashion and art scenes, modern architecture, and status as an important economic and financial center.
  • E. Bonn-Duisdorf
    Bonn-Duisdorf is a district in the western part of Bonn, Germany, characterized by residential areas and local commercial infrastructure.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e510024481908415c0d616fa6186 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e6407c52c081908704d3a4dd6e853b completed April 20, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:43 p.m.