Triple

T17766568
Position Surface form Disambiguated ID Type / Status
Subject Loire E443522 entity
Predicate containsCity P294 FINISHED
Object Montbrison NE NERFINISHED

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: Montbrison | Statement: [Loire, containsCity, Montbrison]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montbrison
Context triple: [Loire, containsCity, Montbrison]
  • A. Montbrison chosen
    Montbrison is a historic town in central France known as a former capital of the Forez region and for its medieval heritage and regional gastronomy.
  • B. Montfaucon
    Montfaucon is a small municipality in the Jura canton of Switzerland, situated on the Franches-Montagnes plateau.
  • C. Mount Blue
    Mount Blue is a prominent forested peak in western Maine known for its hiking trails, scenic views, and location within Mount Blue State Park.
  • D. Rougemont
    Rougemont is a picturesque Swiss alpine village in the canton of Vaud, known for its traditional chalets, mountain scenery, and proximity to the upscale resort area of Gstaad.
  • E. Roccamorice
    Roccamorice is a small Italian hill town in the Abruzzo region, known for its proximity to the Maiella National Park and historic hermitages.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9edf16c8190a59ebd245d378f4f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e485fccb9881908923564bf319f3c1 completed April 19, 2026, 7:36 a.m.
Created at: April 10, 2026, 10:11 a.m.