Triple

T4400128
Position Surface form Disambiguated ID Type / Status
Subject Nyon District E93594 entity
Predicate containsMunicipality P852 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: [Nyon District, containsMunicipality, Nyon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nyon
Context triple: [Nyon District, containsMunicipality, 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_69b345158c748190a2c040fce2da9980 completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b352cd71ec8190a62320fd072f744f completed March 12, 2026, 11:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfdeaa224c8190a115d8af390eea71 completed March 22, 2026, 12:20 p.m.
Created at: March 12, 2026, 11:28 p.m.