Triple

T11133440
Position Surface form Disambiguated ID Type / Status
Subject Rafael Viñoly E263346 entity
Predicate nationality P2 FINISHED
Object Argentine E5383 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: Argentine | Statement: [Rafael Viñoly, nationality, Argentine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Argentine
Context triple: [Rafael Viñoly, nationality, Argentine]
  • A. Argentina chosen
    Argentina is a large South American nation known for its diverse landscapes from the Andes to the Pampas, its vibrant culture including tango and football, and its capital city Buenos Aires.
  • B. Italian Argentine
    An Italian Argentine is an Argentine citizen or resident of Italian ancestry, reflecting the large-scale Italian immigration that has significantly shaped Argentina’s culture and society.
  • C. Argen
    Argen is a river in southern Germany that flows through the Allgäu region before emptying into Lake Constance.
  • D. Argentina and Paraguay
    Argentina and Paraguay are neighboring South American countries that share extensive cultural, historical, and economic ties along their common border.
  • E. Arguayoda
    Arguayoda is a small rural settlement located within the municipality of Alajeró on the island of La Gomera in Spain’s Canary Islands.
  • 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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8347a248190837e8c26f25f553a completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69e46308d2f481908827d0d569802f89 completed April 19, 2026, 5:07 a.m.
Created at: April 8, 2026, 9:28 p.m.