Triple

T18075946
Position Surface form Disambiguated ID Type / Status
Subject Monte Renoso E432551 entity
Predicate hasNameInFrench P6538 FINISHED
Object Monte Renoso 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: Monte Renoso | Statement: [Monte Renoso, hasNameInFrench, Monte Renoso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monte Renoso
Context triple: [Monte Renoso, hasNameInFrench, Monte Renoso]
  • A. Monte Renoso chosen
    Monte Renoso is a prominent mountain in southern Corsica, France, known for its rugged terrain and scenic alpine landscapes.
  • B. Monte Leone
    Monte Leone is a prominent mountain peak in the central Alps on the border between Switzerland and Italy, known for being the highest summit of the Lepontine Alps.
  • C. Monte Grande
    Monte Grande is a suburban city in the Buenos Aires metropolitan area of Argentina, known as the administrative seat of the Esteban Echeverría Partido.
  • D. Monte Beragon
    Monte Beragon is a charming but morally dubious playboy and love interest in the 1945 film noir "Mildred Pierce," whose relationship with the title character contributes to her downfall.
  • E. Monte Frank
    Monte Frank is a Connecticut attorney and civic leader who ran for governor as a third-party candidate in the 2018 Connecticut gubernatorial election.
  • 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_69d8b9070cac81909fa9473fb1c3f1c7 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4d9f4f76c81909015ae4d66d1c85f completed April 19, 2026, 1:34 p.m.
Created at: April 10, 2026, 10:26 a.m.