Triple

T15299375
Position Surface form Disambiguated ID Type / Status
Subject M2 (Lausanne Metro) E365743 entity
Predicate terminus P388 FINISHED
Object Croisettes E1149170 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: Croisettes | Statement: [M2 (Lausanne Metro), terminus, Croisettes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Croisettes
Context triple: [M2 (Lausanne Metro), terminus, Croisettes]
  • A. Croisettes chosen
    Croisettes is a metro station in Lausanne, Switzerland, serving as the northeastern terminus of the city’s M2 metro line.
  • B. Fagerolles
    Fagerolles is a fictional painter in Émile Zola’s novel "L’Œuvre," representing a commercially successful but artistically compromised contrast to the more idealistic artist Mahoudeau.
  • C. Préverenges
    Préverenges is a Swiss municipality on the shores of Lake Geneva in the canton of Vaud, known for its lakeside setting and residential character.
  • D. Les Chosalets
    Les Chosalets is a small family-friendly ski area near Chamonix in the French Alps, known for its gentle slopes and beginner terrain.
  • E. Gréolières
    Gréolières is a small mountain village in southeastern France, known for its scenic setting in the Alpes-Maritimes and proximity to outdoor activities like hiking and skiing.
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03686bfb8819080ba0caae652170a completed April 16, 2026, 1:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fef89bb46481908f27fa98eb6ac5c3 completed May 9, 2026, 9:04 a.m.
Created at: April 10, 2026, 3:15 a.m.