Triple

T21586404
Position Surface form Disambiguated ID Type / Status
Subject Martín Miguel de Güemes E532661 entity
Predicate citizenship P2 FINISHED
Object Argentina 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: Argentina | Statement: [Martín Miguel de Güemes, citizenship, Argentina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Argentina
Context triple: [Martín Miguel de Güemes, citizenship, Argentina]
  • 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. Argentina and Paraguay
    Argentina and Paraguay are neighboring South American countries that share extensive cultural, historical, and economic ties along their common border.
  • D. Argentina and Chile
    Argentina and Chile are neighboring South American countries that share a long Andean border, diverse climates and landscapes, and deep historical, cultural, and economic ties.
  • E. Argentine
    Argentine is a Paris Métro station in the 16th arrondissement, serving Line 1 near the Avenue de la Grande Armée and the Arc de Triomphe.
  • 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_69e0c46251648190876f0427cf2d321b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeeb6137fc8190840b7c1275e62a1d completed April 27, 2026, 4:51 a.m.
Created at: April 16, 2026, 6:31 p.m.