Triple

T95074
Position Surface form Disambiguated ID Type / Status
Subject Meyrin E1912 entity
Predicate partOf P40 FINISHED
Object Geneva metropolitan area E9225 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: Geneva metropolitan area | Statement: [Meyrin, partOf, Geneva metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geneva metropolitan area
Context triple: [Meyrin, partOf, Geneva metropolitan area]
  • A. Geneva metropolitan area chosen
    The Geneva metropolitan area is the cross-border urban region centered on the city of Geneva, spanning parts of Switzerland and France and functioning as a major international, financial, and diplomatic hub.
  • B. Geneva
    Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
  • C. canton of Geneva
    The canton of Geneva is the westernmost Swiss canton, encompassing the city of Geneva and serving as a major international, diplomatic, and financial hub.
  • D. Zurich
    Zurich is the largest city in Switzerland, known as a global financial hub and cultural center situated on the shores of Lake Zurich.
  • E. Gland, Switzerland
    Gland, Switzerland is a small town on the shores of Lake Geneva that is best known as a global hub for environmental and conservation organizations.
  • 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_69a24d4862f881908cc8b89d3a78031d completed Feb. 28, 2026, 2:04 a.m.
NER Named-entity recognition batch_69a24fd4777c81909ea9b9a6bd4f7ad5 completed Feb. 28, 2026, 2:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2db50ac3881908088683967e9ae9f completed Feb. 28, 2026, 12:10 p.m.
Created at: Feb. 28, 2026, 2:09 a.m.