Triple

T8088196
Position Surface form Disambiguated ID Type / Status
Subject Edwards Lifesciences E188787 entity
Predicate hasRAndDCenter P11730 FINISHED
Object Nyon, Switzerland 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, Switzerland | Statement: [Edwards Lifesciences, hasRAndDCenter, Nyon, Switzerland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nyon, Switzerland
Context triple: [Edwards Lifesciences, hasRAndDCenter, Nyon, Switzerland]
  • A. Lausanne, Switzerland
    Lausanne, Switzerland is a picturesque city on the shores of Lake Geneva known for its role as an Olympic capital and its vibrant cultural and academic life.
  • B. 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.
  • C. Bern, Switzerland
    Bern, Switzerland is the de facto capital of Switzerland, known for its well-preserved medieval old town, political institutions, and cultural heritage.
  • D. Lucerne, Switzerland
    Lucerne, Switzerland is a picturesque city in central Switzerland known for its preserved medieval architecture, lakeside setting on Lake Lucerne, and surrounding mountain scenery.
  • E. Geneva
    Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
  • 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_69ca82b7b3e88190b9041ab0ef28b3cb completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb421c717c819089dd88c30a6401aa completed March 31, 2026, 3:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc65afac4819094282e7d63619111 completed April 2, 2026, 1:28 a.m.
Created at: March 30, 2026, 5:29 p.m.