Triple

T8831991
Position Surface form Disambiguated ID Type / Status
Subject LEAR E210167 entity
Predicate locatedIn P40 FINISHED
Object Meyrin E47537 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: Meyrin | Statement: [LEAR, locatedIn, Meyrin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meyrin
Context triple: [LEAR, locatedIn, Meyrin]
  • A. Meyrin chosen
    Meyrin is a municipality in the canton of Geneva, Switzerland, best known for hosting major CERN facilities including the Super Proton Synchrotron.
  • B. Saanen
    Saanen is a picturesque Swiss village in the Bernese Oberland known for its traditional chalets, alpine scenery, and proximity to the upscale resort town of Gstaad.
  • C. Buochs
    Buochs is a Swiss lakeside municipality known for its scenic setting on Lake Lucerne and proximity to the Alps in central Switzerland.
  • D. Ruetz
    Ruetz is a river in the Stubai Valley of Tyrol, Austria, known for its alpine course through the Stubai Alps before joining the Sill River.
  • E. Saas-Fee
    Saas-Fee is a high-altitude Swiss alpine village and ski resort in the Valais Alps, known for its car-free center, extensive glacier skiing, and dramatic mountain scenery.
  • 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_69ca8365b28081909e48e45e95dfc405 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc604ed2b88190b4f53b34b5a438f7 completed April 1, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf896cf5a8819098a76288bd505c1e completed April 3, 2026, 9:33 a.m.
Created at: March 30, 2026, 6:47 p.m.