Triple

T3014964
Position Surface form Disambiguated ID Type / Status
Subject Linac1 E82315 entity
Predicate locatedInCity 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: [Linac1, locatedInCity, Meyrin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meyrin
Context triple: [Linac1, locatedInCity, 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. 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.
  • C. Thun
    Thun is a historic Swiss town in the canton of Bern, known for its medieval old town, lakeside setting on Lake Thun, and views of the surrounding Alps.
  • D. Veytaux
    Veytaux is a small municipality on the shores of Lake Geneva in the canton of Vaud, Switzerland, known for its scenic setting and proximity to the historic Château de Chillon.
  • E. Meiringen
    Meiringen is a Swiss alpine town in the Bernese Oberland, known for its dramatic mountain scenery, Reichenbach Falls, and association with Sherlock Holmes.
  • 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_69ad8b1eb53481908c39bbcd1ec104b2 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a69e8148190a97507740c9d26a8 completed March 8, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e6b78448190beb41460314278ec completed March 11, 2026, 8:57 a.m.
Created at: March 8, 2026, 3 p.m.