Triple

T1123753
Position Surface form Disambiguated ID Type / Status
Subject Léman Express E24670 entity
Predicate terminus P388 FINISHED
Object Genève E414 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: Genève | Statement: [Léman Express, terminus, Genève]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Genève
Context triple: [Léman Express, terminus, Genève]
  • A. Geneva chosen
    Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
  • 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. Neuchâtel
    Neuchâtel is a French-speaking canton in western Switzerland known for its lakeside capital, watchmaking industry, and historic architecture.
  • D. Nyon
    Nyon is a Swiss town on the shores of Lake Geneva that serves as the administrative home of several major sports organizations, including UEFA.
  • E. Montreux
    Montreux is a picturesque resort town in southwestern Switzerland, renowned for its lakeside promenade, mild microclimate, and the annual Montreux Jazz Festival.
  • 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_69a4940712c88190aa244f3fc6070a65 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bbc09e708190b099d436d1f737eb completed March 1, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37371fbc08190abc2d3a1dd2f4e9a completed March 13, 2026, 2:16 a.m.
Created at: March 1, 2026, 7:44 p.m.