Triple

T6211205
Position Surface form Disambiguated ID Type / Status
Subject Vich E138873 entity
Predicate locatedNear P294 FINISHED
Object Nyon E75171 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: Nyon | Statement: [Vich, locatedNear, Nyon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nyon
Context triple: [Vich, locatedNear, Nyon]
  • A. Nyon chosen
    Nyon is a Swiss town on the shores of Lake Geneva that serves as the administrative home of several major sports organizations, including UEFA.
  • B. Lausanne
    Lausanne is a major Swiss city on the shores of Lake Geneva, known for hosting the International Olympic Committee and its vibrant cultural and academic institutions.
  • C. Geneva
    Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
  • D. Geneva
    Geneva is a small city in northeastern Ohio situated along Lake Erie, known for its wineries, tourism, and location within the Rust Belt region.
  • E. Geneva
    Geneva is a small city in New York's Finger Lakes region, known for its lakeside setting on Seneca Lake and its historic colleges and wineries.
  • 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_69c008ada364819096c9e92c74d639b5 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062896f3881909f264bb45badc5d0 completed March 22, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8d66fdb1c81909ca125e5918b0997 completed March 29, 2026, 7:36 a.m.
Created at: March 22, 2026, 4:21 p.m.