Triple

T11991496
Position Surface form Disambiguated ID Type / Status
Subject Mika Rottenberg E285416 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: [Mika Rottenberg, nationality, Argentine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Argentine
Context triple: [Mika Rottenberg, 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. Argentina
    Argentina is a genus of flowering plants in the rose family (Rosaceae), commonly known for species resembling cinquefoils and often found in temperate and alpine regions.
  • C. 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.
  • D. Argen
    Argen is a river in southern Germany that flows through the Allgäu region before emptying into Lake Constance.
  • E. Argentina and Paraguay
    Argentina and Paraguay are neighboring South American countries that share extensive cultural, historical, and economic ties along their common border.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903afe4388190a2cf2328e85adf9b completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f48abcf2588190a44e6e31e045b356 completed May 1, 2026, 11:13 a.m.
Created at: April 8, 2026, 9:46 p.m.