Triple

T17867741
Position Surface form Disambiguated ID Type / Status
Subject La Salle E446747 entity
Predicate hasLocalName P6353 FINISHED
Object La Salle — 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: La Salle | Statement: [La Salle, hasLocalName, La Salle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: La Salle
Context triple: [La Salle, hasLocalName, La Salle]
  • A. La Salle
    La Salle is a small alpine municipality in Italy’s Aosta Valley, known for its scenic mountain landscapes and proximity to Mont Blanc.
  • B. La Salle
    La Salle was the former name of the French industrial town now known as Decazeville, historically associated with coal mining in the Aveyron department.
  • C. La Salle
    La Salle is a notable neighborhood or sector within Bogotá’s Chapinero locality, recognized for its educational institutions and urban residential character.
  • D. de La Salle
    De La Salle is a French surname most famously associated with Jean-Baptiste de La Salle, the Catholic priest and educational reformer who founded the Institute of the Brothers of the Christian Schools.
  • E. La Salle College
    La Salle College is a prestigious boys' secondary school in Hong Kong known for its strong academic performance and prominent alumni in politics, business, and public service.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d8b9f4c22c819093c2680434472894 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49aa0b69081909fba3b42d237b543 completed April 19, 2026, 9:04 a.m.
Created at: April 10, 2026, 10:17 a.m.