Triple

T7783177
Position Surface form Disambiguated ID Type / Status
Subject canton of Fribourg E187173 entity
Predicate containsTown P847 FINISHED
Object Kerzers E302978 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: Kerzers | Statement: [canton of Fribourg, containsTown, Kerzers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kerzers
Context triple: [canton of Fribourg, containsTown, Kerzers]
  • A. Kerzers chosen
    Kerzers is a municipality in the canton of Fribourg in western Switzerland, known for its bilingual character and proximity to the Papiliorama butterfly and tropical gardens.
  • B. Kehler
    Kehler is a German-origin surname borne by various individuals, including American Air Force general C. Robert Kehler.
  • C. Kuppenheimer
    Kuppenheimer was a prominent American men's clothing company best known for its high-quality suits and influential early 20th-century advertising campaigns.
  • D. Balke
    Balke is a Norwegian surname most notably associated with the 19th-century landscape painter Peder Balke.
  • E. Kremmen
    Kremmen is a small town and municipality in the Oberhavel district of the German state of Brandenburg.
  • 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_69ca82af2d2c8190963861f5e0b8bf21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cadf1f9c648190ac2b06d0d54035ea completed March 30, 2026, 8:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69caf5e400d881909d6cdeb7eaac3a59 completed March 30, 2026, 10:15 p.m.
Created at: March 30, 2026, 4:22 p.m.