Triple

T10938744
Position Surface form Disambiguated ID Type / Status
Subject Canton of Neuchâtel E258406 entity
Predicate highestPoint P210 FINISHED
Object Chasseral E189917 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: Chasseral | Statement: [Canton of Neuchâtel, highestPoint, Chasseral]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chasseral
Context triple: [Canton of Neuchâtel, highestPoint, Chasseral]
  • A. Chasseral chosen
    Chasseral is a prominent mountain in the Jura range of western Switzerland, known for its panoramic views and telecommunications installations.
  • B. Lussy
    Lussy is a small municipality in the Glâne District of the canton of Fribourg in western Switzerland.
  • C. Chavornay
    Chavornay is a municipality in the canton of Vaud in western Switzerland, known for its rural character and location in the Orbe plain.
  • D. Saignelégier
    Saignelégier is a municipality in the Swiss canton of Jura known for its rural landscapes, watchmaking heritage, and the annual Marché-Concours horse festival.
  • E. Chassieu
    Chassieu is a commune in the Metropolis of Lyon in eastern France, known for its residential areas and proximity to the Lyon urban center.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770b12a9881909305db49aa554a1b completed April 9, 2026, 9:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3446b6f1481908365bb9235768859 completed April 18, 2026, 8:44 a.m.
Created at: April 8, 2026, 9:23 p.m.